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Honeycomb materials are often used as the inner core of composite sandwich structures and are widely applied in impact resistance equipment design. Inspired by biomimetic materials, a series of potential variable thickness honeycombs with enhanced biomimetic cells (VTHEBs) are proposed and analyzed in this study, including the variable thickness honeycomb with bionic circular cells (VTHBC), the variable thickness honeycomb with bionic triangular cells (VTHBT), and the variable thickness honeycomb with bionic hexagonal cells (VTHBH). The crashworthiness properties of VTHEBs are studied by experimental, numerical, and theoretical analysis. The experimental results reveal the mechanical responses of VTHEBs under out-of-plane loading and validate the numerical models established by LS-DYNA. It is also observed that VTHBC shows better crashworthiness than VTHBT and VTHBH. Compared with the corresponding regular variable thickness honeycomb (RVTH), the variable thickness honeycomb with enhanced bionic cells has superior material distribution, which helps to improve the crushing force level and energy absorption potential. Besides, the numerical models are used to explore the effects of different design parameters (thickness deviation coefficient, cell size coefficient) on the mechanical performances of VTHEBs. Finally, the theoretical models of crushing forces are derived to predict the crushing performances of VTHEBs. The results show that the theoretical models can approximate the overall trend of experimental and numerical results with acceptable accuracy. This study provides an interesting design concept for superior crashworthy structures, which can be expected to be applied to impact resistance equipment in the future.

Based on the mechanical characteristics of the core layer, which withstands the shear stress and deformation of a sandwich beam, a topology optimization framework based on the bi-directional evolutionary structural optimization method is proposed to optimize the core layer composed of a periodic base cell with extreme shear stiffness. The effects of the volume fraction, filter radius, and initial periodic base cell (PBC) aspect ratio on the micro-topology of the core and the dynamic response process, core compression, and energy absorption capacity of the sandwich beams under blast impact loading were analyzed by the finite element method. The results demonstrated that the over-pressure action stage was coupled with the core compression stage. Under the same loading and mass per unit area, the sandwich beam with a 20% volume fraction core layer had the best blast resistance. The filter radius has a slight effect on the shear stiffness and blast resistances of the sandwich beams, but increasing the filter radius could slightly improve the bending stiffness. Upon changing the initial PBC aspect ratio, there are three methods for PBC evolution: the first is to change the angle between the adjacent bars, the second is to further form holes in the bars, and the third is to combine the first two methods. However, not all three methods can improve the energy absorption capacity of the structure. Changing the aspect ratio of the PBC arbitrarily may lead to worse results. More detailed studies are necessary if further optimization is to be achieved.

Despite significant advances in the design optimization of bone scaffolds for enhancing their biomechanical properties, the functionality of these synthetic constructs remains suboptimal. One of the main challenges in the structural optimization of bone scaffolds is associated with the large uncertainties caused by the manufacturing process, such as variations in scaffolds' geometric features and constitutive material properties after fabrication. Unfortunately, such non-deterministic issues have not been considered in the existing optimization frameworks, thereby limiting their reliability. To address this challenge, a novel multiobjective robust optimization approach is proposed here such that the effects of uncertainties on the optimized design can be minimized. This study first conducted computational analyses of a parameterized ceramic scaffold model to determine its effective modulus, structural strength, and permeability. Then, surrogate models were constructed to formulate explicit mathematical relationships between the geometrical parameters (design variables) and mechanical and fluidic properties. The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) was adopted to generate the robust Pareto solutions for an optimal set of trade-offs between the competing objective functions while ensuring the effects of the noise parameters to be minimal. Note that the nondeterministic optimization of tissue scaffold presented here is the first of its kind in open literature, which is expected to shed some light on this significant topic of scaffold design and additive manufacturing in a more realistic way.

Thin-walled hat-shaped structures have gained growing interest attributed to their excellent performance and wide application in the vehicle industry. However, few systematic studies have been conducted on the design of hat-shaped structures with irregular sectional shapes. In present research, thin-walled double-hat beam (DHB) with different sectional configurations under dynamic three-point-bending are investigated by performing numerical simulations. First, the energy absorption mechanism of DHB is explored, and then an in-depth parametric study, including shape parameters o, p, q and thickness parameter k, is performed. The results show that all DHBs deform in bending with indentation mode. And compared with single-hat beam (SHB), the DHB has a significant advantage in loading capacity. When the design space is held fixed, the shape parameter o has the greatest influence on the bending behaviors of DHB, followed by parameter p, while parameter q has the least influence. In addition, it is also found that a larger thickness of the top hat leads to the increase of the SEA and PCF and the decrease of the hammer displacement. Finally, a multi-objective optimization based on lower confidence bound matrix (LCBM) criteria is conducted to determine the optimal design of DHB. The numerical results of the optimal DHB suggest that increasing the initial impacting velocity will make the SEA and PCF increase while make the displacement decrease.

Many unavoidable uncertainties in the engineering structure will affect its performance response. It is necessary to analyze the uncertain responses generated by uncertain factors in the vehicle design. Therefore, this study proposes a feasible identification method of uncertainty responses for vehicle structures. The proposed method consists of radial basis function neural network (RBFNN) and Taylor interval expansion (IE) model. The optimal network parameters of RBFNN are trained by the improved K-means clustering algorithm and singular value decomposition (SVD). Here, the first-order and second-order differential equations are derived from the RBFNN parameters since it is difficult to calculate the partial derivatives of complex systems without explicit expressions. A series of typical functions are tested and the results show that the trained RBFNN parameters can approximate the first-order and second-order partial derivatives of different types of functions. Besides, the subinterval expansion method is further applied to improve the calculation accuracy of uncertain structural responses. Finally, the proposed method is applied to four engineering applications (vehicle hood, mechanical claw, anti-collision structures, and multi-link suspension). Compared with genetic algorithm (GA) and Monte Carlo simulation (MCS), the proposed method can improve computational efficiency while ensuring accuracy. The identification method of interval uncertainty responses can be used as an alternative for uncertainty analysis and subsequent reliability or robustness optimization.

Growth and energy budget of marine amphipod juvenile Eogammarus possjeticus at different temperatures (20°C, 24°C, 26°C, 28°C, 30°C, 32°C and 34°C) were investigated in this study. The results showed that the cumulative mortality rate increased significantly with rising temperature (p

Ocean acidification is predicted to have significant implications for marine calcifying organisms. However, little is known about the physiological responses of Pacific oyster, Crassostrea gigas, to elevated partial pressure of atmospheric carbon dioxide (pCO2) under natural fluctuations associated with a farm environment. The present study evaluated the effect of two pCO2 levels (i.e. ambient ∼625 μatm and elevated ∼1432 μatm) on the physiological processes and growth of C. gigas in in situ mesocosms that simulated the farm environment. Oysters were exposed for 30 days over a sensitive period during their production cycle when they are first exposed to natural coastal conditions. Despite this being a well-known “bottleneck” in production, it remains understudied with respect to climate change. Results showed that elevated pCO2 levels decreased clearance rate, ingestion rate, absorption efficiency, and oxygen to nitrogen ratio, while increasing oxygen consumption and ammonia-N excretion rates. These physiological responses of oysters resulted in a reduction in energy available for growth (scope for growth). No mortality was observed in the control or elevated pCO2 treatments, indicating that although oyster may survive future coastal acidification, the allocation of energy towards production within aquaculture systems will decrease in the future, affecting the culture of these economically important marine bivalves.

The Ria de Aveiro is an important coastal lagoon for wildlife in Portugal, where the production of bivalves reaches approximately 2700 tonnes annually. However, the illegal overfishing of bivalves is frequent in this lagoon, which causes critical changes in the ecosystem. In this study, using a developed food-web model (Ecopath model), the ecological carrying capacity and maximum sustained yield of bivalve filter feeders were estimated, and further increases in bivalve biomass in other species groups were investigated. The results showed that 1) the current biomass and legal catch of bivalves do not yet exceed the ecological carrying capacity (177.84 tonnes km− 2) or the maximum sustained yield (88.92 tonnes km− 2 year− 1) in Ria de Averio; 2) the harvested bivalves of the maximum sustained yield represent removing from the ecosystem ~ 581 tonnes carbon (C) and ~ 83 tonnes nitrogen (N) annually, with substantial ecological and economic implications; and 3) a further increase in the biomass levels of bivalves may cause the ecotrophic efficiency of other groups to become unrealistic, potentially leading to decreases in ecosystem transfer efficiency, biodiversity and health. The results here are expected to guide the sustainable development and management of bivalves in Ria de Averio and the protection of the local environment.

This study proposes a novel topology optimization approach for design of continuous steering fiber path for composite structures using a level set method. The radial basis function (RBF) is employed to construct the level set function (LSF). Fiber orientations are parameterized by LSF and fiber paths can be determined instinctively for the inherent advantages of the level set approach. Besides, the fast-marching method is employed to extrapolate the primary fiber paths to the secondary fiber paths, which can avoid the manufacturing drawbacks such as gaps and overlaps to a large extent. A detection and filtering technique is proposed here to alleviate the orientation disorder at the intersection of the diffusion surfaces. Two design schemes are developed to optimize both structural topology and fiber path. In a sequential procedure, topology optimization is conducted first with isotropic materials; and then fiber paths are optimized on the basis of fixed topological boundary. In a simultaneous optimization procedure, structural boundaries and fiber paths are optimized alternately through two inner loops. In this study, three numerical examples are presented to demonstrate the effectiveness of the proposed methods, and the results show that optimization of fiber path is beneficial to improvement of structural performance. In general, the simultaneous optimization scheme exhibits better optimal outcome in comparison with the sequential optimization scheme.

To accurately and quickly predict the open-circuit air-gap magnetic field in interior permanent magnet synchronous machines (IPMSMs), an analytical model based on magnetic equivalent circuit (MEC) method is proposed. The analytical model can provide radial and tangential components of open-circuit magnetic field in the slotless air gap. The radial component is obtained from the MEC model, and the tangential component is obtained from boundary conditions of macroscopic equations. Then, a complex relative air-gap permeance is applied to take the effect of slots into account. As a result, an accurate solution of both radial and tangential components of the flux density in the slotted air gap is obtained. Additionally, the no-load back electromotive force (EMF) and cogging torque are calculated based on the open-circuit air-gap magnetic field. All the analytical results are verified by the finite element (FE) analysis and they are well matched. In the end, a direct measurement experiment of open-circuit air-gap magnetic field is proposed to verify the validity of both radial and tangential open-circuit air-gap magnetic fields.

To improve the separation efficiency of photogenerated carriers, heterogeneous photocatalysts were prepared and characterized in this work. First, graphitic carbon nitride (g-C3N4) and bismuth molybdate (Bi2MoO6) were synthesized by thermal polymerization and a hydrothermal method, respectively. Then, Bi2MoO6/g-C3N4 composites with different mass ratios were constructed by a facile method. The microstructure and morphology of the composites were characterized and analyzed. The results showed that Bi2MoO6/g-C3N4 heterostructures were formed in the composite. Taking rhodamine B as the target pollutant, the photo-degradation performances of the composite were evaluated. The experimental results indicated that the composite with a Bi2MoO6/g-C3N4 mass ratio of 0.1 : 0.9 exhibited excellent photocatalytic performance. The results demonstrated that the band structure of g-C3N4 and Bi2MoO6 can promote the migration of photogenerated carriers, and then reduce the recombination rate of photogenerated electrons and holes. In the photocatalytic process, superoxide free radicals played a major role.

The effects of three environmental factors, salinity, carbonate alkalinity, and pH, on the survival, feeding, and respiratory metabolism of Eogammarus possjeticus (Amphipoda: Gammaridae) were investigated experimentally. The results show that E. possjeticus could tolerate a broad salinity range. The 24-h lowest median lethal salinity was 2.70, and the highest was 47.33. The 24-h median lethal alkalinity and pH were 23.05 mmol/L and 9.91, respectively; both values decreased gradually with time. Different values of salinity, carbonate alkalinity, and pH resulted in significant differences in the cumulative mortality (P

An eccentric position diagnosis method of static eccentricity (SE) fault of external rotor permanent magnet synchronous motor (ER-PMSM) is presented. Firstly, an analytical model of no-load radial magnetic field of ER-PMSM is established. Analytical models of no-load Back-EMF of both unit motors and the whole motor are carried out and are verified by finite element method (FEM) and experimental measurements. Then, the influences of SE ratio, SE circumferential angle, winding distribution mode and number of parallel branches on no-load radial magnetic field and no-load Back-EMF are analyzed based on these analytical models. The results show that SE does not affect the frequency characteristics of no-load radial magnetic field, but changes space order characteristics. On one hand, for ER-PMSM, of which the number of unit motors is equal to 1, SE causes no-load Back-EMF distortion. On the other hand, for ER-PMSM, of which the number of unit motors is greater than 1, SE does not affect no-load Back-EMF of the whole motor, but it still leads to no-load Back-EMF distortion of unit motors. Therefore, based on total harmonic distortion (THD) of no-load Back-EMF of unit motor, a projection method of intersection lines for SE fault diagnosis of ER-PMSM is proposed finally.

In this study, the air gap magnetic field characteristics of external rotor permanent magnet synchronous motors (PMSMs) under both the stator and rotor coordinate systems considering low-order current harmonics and high-order sideband current harmonics are analysed. A direct measurement technique (DMT) for air-gap magnetic field is proposed. First, an analytical model of air gap magnetic field of external rotor PMSMs is established. The spatial order and frequency characteristics of stator/rotor air gap magnetic field are revealed. Then, a 24-pole 27-slot external rotor PMSM is taken as an example. The analytical and finite element (FE) results are compared and analysed. The difference of the spatial order and frequency characteristics between the stator and rotor air gap magnetic field are verified. Next, a new DMT is proposed, which can detect the precise distribution and local microscopic characteristics on the order of 10−1 mm with high resolution. The accuracy of analytical and FE model are verified by the DMT and an indirect experimental test of no-load back electromotive force. Finally, the mechanical challenges of in-wheel motors and the practicablility of DMT for eccentricity detection are further discussed.

Aquaculture is a rapidly increasing industry, and managers in China are searching sustainable development in the context of much more intensive culture. Our study area focused on an embayment that exposed to suspended culture of oysters. Impact of oyster expansion was evaluated in the context of ecosystem which do not limits to the phytoplankton−oyster relationship but other interspecific relations by the use of food web model. Following recently proposed measures, the ecological carrying capacity (ECC) was defined as the maximum amount of oyster biomass that would not yet cause ecosystem function to depredate beyond their resilience capacity, i.e., not to cause any other group’s biomass to fall below 10% of its original biomass. The result suggests that an increase of oyster biomass caused negative impact on the ecosystem in terms of biomass of the most of functional groups and ecosystem indicators such as flow diversity and transfer efficiency. The ECC of oyster in suspended culture was 976 t km−2 (1.8 times of present biomass), and exceeding the levels will cause zooplanktivorous fish biomasses to fall below the 10% threshold. The ecosystem-based ECC assessment method in the present simulation dynamically predicted the impact of oyster development on other organisms in the environment to guide the sustainable development of bivalve culture in Sanggou Bay and provides an approach for the assessment of bivalve ECC in other parts of the world.

In this study, two novel foam-filled hierarchical structures are proposed, namely foam-filled square hierarchical tubes (FSHT) and foam-filled circular hierarchical tubes (FCHT). First, dynamic FEA models of the foam-filled hierarchical tubes are established by LS-DYNA and validated against experimental data. The mechanical behaviors of the foam-filled hierarchical tubes under axial load are investigated. The results show that novel foam-filled hierarchical tubes have better crashworthiness performances than conventional foam-filled square tubes (FST) and foam-filled circular tubes (FCT). Then, the theoretical solution of energy absorption is developed, and its accuracy is validated. Next, the design parameters (foam density and thin-wall thicknesses) of FSHT and FCHT are analyzed by orthogonal array design, and the effects of design variables on crashworthiness are studied. Finally, to obtain the optimal design parameters of FSHT and FCHT, the robust optimization method considering the manufacturing uncertainty is implemented by employing the interval uncertainty model (IUM) and the feedforward neural network (FNN). Structures obtained with the proposed robust optimization method are of more stable performance compared with the traditional deterministic optimization counterparts. The findings provide a hybrid design combining hierarchical tubes with foam fillers with superior crashworthiness performance for energy-absorbing devices, and the robust optimization method can be used to design efficient lightweight crashworthy structures.

The slamming acoustic of a vehicle door is objectively not associated to the inherent character of the automobile, however, it is associated to the inherent structure of the vehicle door, which is a vital subjective performance to evaluate the vehicle. Although it has been recognized that static indicators may engender an inferior design result in engineering practice, the majority studies in the literature have not considered dynamic indicators for the door slamming event. This paper presents a multi-objective optimization (MOO) framework of a vehicle door design in the slamming event for optimal dynamic performances. In our previous study we have obtained the transient excitation forces through the transfer path analysis (TPA), lab experiment and bench test. These transient excitation forces will be the input for the MOO algorithm. The dimensions of the vehicle door structure main components are considered as design variables. The objective functions include the first natural frequency obtained by semi-constrained modal analysis, the mass of the vehicle door, and the maximum amplitude of the target points on the vehicle door’s glass. The constraint functions include the design variable bounds, dynamic stiffness constraints of the four mounting points for the glass run channel system. In order to promote the efficiency of subsequent optimization, the response surface method (RSM) is employed instead of time-consuming finite element method. The multi-objective particle swarm optimization (MOPSO) algorithm is implemented to conduct the dynamic indicators optimization. The results show that the proposed optimization framework is successful of achieving a reliable solution with a uniformly distributed Pareto boundary, and it is recommended to choose an optimal result from relatively insensitive regions that meet the requirements. It is shown that the simulation response of the optimized door structure can reduce the acoustic pressure amplitude at the driver’s right ear employed BEA technique. The proposed framework can be adapted to optimize door structural design for any vehicle door to improve noise, vibration, and harshness (NVH) performance.

Cooling regimes have a significant effect on the mechanical properties of ultra-high performance concrete (UHPC) after exposure to elevated temperatures. Load-bearing structures are easily subjected to the coupling action of static and dynamic loads in the fire. This study investigated the dynamic behavior and failure characteristics of UHPC after exposure to heating-cooling treatments. The variations in the P-wave velocities, compressive strengths , elastic modulus and dynamic increase factor (DIF) of the specimens in terms of the different cooling regimes (natural cooling, water cooling) were analyzed. The experimental results indicated that as compared to natural cooling, water cooling caused significant losses in the P-wave velocities, quasi-static and dynamic compressive strength, and dynamic elastic modulus due to the thermal shock induced by water cooling. As the target temperature increased from 250 to above 500 °C, the difference of mechanical property losses varied from small to large, indicating that the thermal shock induced by water cooling caused insignificant damage to the specimen at 250 °C, whereas considerable damage was induced to the specimen above 500 °C. Water cooling enhanced the DIF values of the specimens below 500 °C, but reduced the DIF values at 750 °C. Axial static-pressure loading improved the mechanical properties of the specimen when UHPC was in the elastic phase, which could be attributed to the initial microcracks and pores closed and compacted by the axial static-pressure. However, when the axial static-pressure exceeded the elastic limit of UHPC, microcracks were prone to expansion under impact loads and the mechanical properties of the specimens deteriorated rapidly. Likewise, the failure pattern of the specimen under a given impact load was mainly determined by the heating temperature and cooling regime, whereas the axial static-pressure loading could only affect the fragment size.

To improve the impact resisting performance of reinforced concrete (RC) components, three strengthening designs based on ultra-high performance concrete (UHPC) are proposed in this study. Drop hammer impact test was conducted to evaluate the dynamic response and failure modes of RC beams and UHPC strengthened RC-UHPC beams. Test specimens included two control RC beams, a RC beam with UHPC layer retrofitted on the tension surface, a RC beam with UHPC layers retrofitted on both the compression and tension sides, two RC beams with UHPC layer that was not directly attached to the tension surface, but with 5 mm gap between the interfaces. Test results showed UHPC strengthened beams had a good impact resistance. Under the impact from 641 kg weight dropping from 0.5 m, with a 15 mm UHPC layer directly attached to the tension surface of the RC beam, the crack pattern shifted from concrete spalling to diagonal shear failure, and the maximum and residual displacements decreased by 9.1% and 25.3%, respectively. RC-UHPC beams with non-attached interfaces exhibited even better impact resistance, the UHPC layer was able to develop multiple energy dissipating tensile cracks prior to failure, and the gap ensured a larger moment resistance leading to reduced beam deflections. The repeated impacts were performed on RC-UHPC beams. With the same total impact energy, the single impact was found to be more hazardous than the repeated impacts. Nonlinear finite element modelling was developed to further interpret the experimental results. With the validated numerical model, energy absorption curves, dynamic shear force and bending moment distribution diagrams were derived. Based on the experimental and numerical data, the shear mechanisms of RC beams and RC-UHPC beams were studied. The effects of non-attached spacing length, spacing depth and UHPC layer thickness were investigated in the parametric study.

This study proposes a machine learning (ML) based approach for optimizing fiber orientations of variable stiffness carbon fiber reinforced plastic (CFRP) structures, where neural networks are developed to estimate the objective function and analytical sensitivities with respect to design variables as a substitute for finite element analysis (FEA). To reduce the number of training samples and improve the regression accuracy, an active learning strategy is implemented by successively supplying effective samples along with the suboptimal process. After proper training of neural networks, a quasi-global search strategy can be applied by implementing a large number of initial designs as starting points in the optimization. In this article, a mathematical example is first presented to show the superiority of the active learning strategy. Then a benchmark design example of a CFRP plate is scrutinized to compare the proposed ML-based with the conventional FEA-based discrete material optimization (DMO) method. Finally, topology optimization of fiber orientations is performed for design of a CFRP engine hood, in which the structural performance generated from the proposed ML-based approach achieves 12.62% improvement compared with that obtained from the conventional single-initial design method. This article is anticipated to demonstrate a new alternative for design of fiber-reinforced composite structures.

Majority of existing design optimization of bumper systems has focused on one single impact loading case in literature, which may not offer proper performance under other loading cases. This study aims to address this issue by developing a multiobjective optimization approach, in which multiple impact loading scenarios are considered to optimize the intrusion and energy absorption of the bumper system. Modeling of real-life impact scenarios is first validated by comparing the numerical results with the experimental data. Based upon the Latin hypercube design (LHD) and Kriging surrogate approaches, energy absorption ( E A ) and maximum intrusion ( M I ) are formulated in terms of design variables to consider the structural crashworthiness and repair/maintenance cost, respectively. In order to generate Pareto solution in the multiobjective optimization effectively, the recently developed Kriging Believer based parallelized efficient global optimization (EGO) algorithm is adopted to optimize the bumper system subject to three impact loads, namely the low-speed sled crash, dynamic three-point bending and 40% offset impact, respectively. These different load cases are considered through a weighted average scheme. The optimization results indicate that the Pareto solutions largely depend on the assignment of weight factors to different load cases. In order to generate more reasonable results, the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) database is also used to determine the weighting factors for each loading case. It is found that for the intrusion objective, the design under the multiple impact loads offers an intrusion reduction of 20.27% in the sled crash, 5.84% in the 40% offset impact, in comparison with the baseline design. The intrusion of three-point bending is the same as that of baseline design to compromise other more frequently occurring load cases. For the energy absorption objective, although the design leads to increase in EA by 3.01% in the sled crash and 1.79% in 40%-offset impact, the performance in the three-point bending is actually sacrificed to compromise the other more frequently occurring load cases. The study help gain insights into the design optimization of a bumper system for real-life automotive engineering.

In engineering practice, most optimization problems have multiple objectives, which are usually in a form of expensive black-box functions. The multiobjective efficient global optimization (MOEGO) algorithms have been proposed recently to sequentially sample the design space, aiming to seek for optima with a minimum number of sampling points. With the advance in computing resources, it is wise to make optimization parallelizable to shorten the total design cycle further. In this study, two different parallelized multiobjective efficient global optimization algorithms were proposed on the basis of the Kriging modeling technique. With use of the multiobjective expectation improvement, the proposed algorithm is able to balance local exploitation and global exploration. To implement parallel computing, the “Kriging Believer” and “multiple good local optima” strategies were adopted here to develop new sample infill criteria for multiobjective optimization problems. The proposed algorithms were applied to five mathematical benchmark examples first, which demonstrated faster convergence and better accuracy with more uniform distribution of Pareto points, in comparison with the two other conventional algorithms. The best performed “Kriging Believer” strategy approach was then applied to two more sophisticated real-life engineering case studies on the tailor-rolled blank (TRB) structures for crashworthiness design. After optimization, the TRB hat-shaped tube achieved a 3% increase in energy absorption and a 10.7% reduction in mass, and the TRB B-pillar attained a 10.1% reduction in mass and a 12.8% decrease in intrusion, simultaneously. These benchmark and engineering examples demonstrated that the proposed methods are fairly promising for being an effective tool for a range of design problems.

Integrated Multi-Trophic Aquaculture (IMTA) is an effective method for sustainable aquaculture as species from different trophic levels could reduce negative effects from fed species in the environment. A proper proportion of different trophic species in an IMTA system could improve the aquaculture production and environmental sustainability. At present, research on the proper proportions for farming species is scarce. We investigated the effects of IMTA modes of oyster (Crassostrea gigas) and kelp (Saccharina japonica) in different weight ratios on water quality and carbonate system in a closed enclosure experiment for three days in the Sanggou Bay in Shandong Province, China, in December 2017. Nine collocation modes in oyster:kelp weight ratio were tested showing as 24:3, 24:2, 24:1, 16:3, 16:2, 16:1, 8:3, 8:2, and 8:1. The water parameters were determined at 17:00 on Day 1 (D1), and 6:00 and 17:00 on Days 2 (D2) and 3 (D3). As two-way ANOVA showed, all increased parameters (dissolved oxygen (DO), pH, chl a, the carbonate system and p CO2) were significantly related to oyster-kelp modes, and interaction between modes and time were also significant (P

This paper introduces a novel hierarchical core structure to sandwich panel for bearing the blast loading, in which each vertex of a regular hexagonal cell was replaced with a smaller hexagonal unit. The finite element (FE) models of such hierarchical honeycomb sandwich panels were established and validated with the experiments under different impulse loads. The hierarchical honeycomb cores were compared with the regular honeycomb counterpart in terms of the peak deflection on the back facesheet, compression and specific energy absorption (SEA) of the core. The results showed that the maximum deflection at the back facesheet of the hierarchical honeycomb sandwich panels were smaller than the regular honeycomb counterpart for a higher level of blast load (specifically, the dimensionless impulse higher than 0.06). It was found that the structural hierarchical parameter γ (i.e. the ratio of the newly-introduced smaller hexagonal edge length (L1) to the regular hexagon edge length (L0)), had limited influence on the maximum deflection of back facesheet of the sandwich panel, but had a significant effect on the SEA of the cores.

Scallop farming is the main economic activity in the northern parts of China, with a production that has increased quickly since the 1980s. In the present study, a bioenergetics growth model to the Yesso scallop, Patinopecten yessoensis, in the mariculture area of Zhangzidao Island was applied, based on dynamic energy budget (DEB) theory which describes energy flux variation through different compartments of the scallop body. Estimates of most DEB parameters were based on available physiological data or published information, and the two parameters, i.e., detritus contribution to food (αDet) and half-saturation constant for food (XK) were calibrated using datasets in this study. The model relied on two forcing variables: water temperature and food density expressed by different food quantifiers. The sets of data used to validate the model came from a growth experiment performed on P. yessoensis for bottom-sowing culture. The DEB model developed here for P. yessoensis was allowed to simulate growth and reproduction of the scallop in the growing area of the Zhangzidao Island.

The phase field modelling has been extended from brittle fracture to ductile fracture by incorporating plasticity. However, the effects of plastic yield functions and hardening on the fracture behaviour have not been examined systematically to date. The phase field fracture coupled with multi-surface plasticity is formulated in the variational framework for the unified yield criterion, which is able to facilitate the study on different yield surfaces. First, the homogeneous solutions of fracture in elasto-plastic solids are derived analytically for 1D and 2D cases. The results show that a greater hardening modulus would lead to an ascending branch of the stress versus strain curve; and the yield function may significantly affect the stress state and phase field damage. Second, the finite element (FE) technique is implemented for modelling the phase field fracture in elasto-plastic solids, in which the stress update and consistent tangent modular matrix are derived for the unified yield criterion. Finally, three numerical examples are presented to explore the effects of the yield function and material hardening. It is found that the yield function and material hardening could significantly affect the crack propagation and the final fracture pattern. In particular, the Tresca yield function tends to create a straight crack path orthogonal to the first principal stress, while the other yield functions show no sizeable difference in their crack paths.