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As the weakest segment within frozen soil, the interface between ice and frozen soil undertakes the link of load transmission. The mechanical parameters between ice and frozen soil influence the deformation and strength of frozen soil. To investigate the mechanical behaviors of ice-frozen soil interface, the cryogenic direct shear tests were carried out and the deformation, strength properties of interface were analyzed. The shear stress of interface was described by generalized hyperbolic model and the physical meaning of the model parameters were defined. Based on the generalized hyperbolic model, the shear stiffness of interface was derived. The effect of temperature on the strength, shear stiffness of interface under different initial moisture contents, initial void ratios and normal stresses were discussed. The three-dimensional finite element model was established using COMSOL Multiphysics, and the mechanical behaviors of ice frozen soil interface were researched.

This paper proposed a coupled model of effective feature extraction and optimized classifier, which can overcome the existing problems of coal and gas outbursts classification in the literatures. Firstly, we support the use of kernel principal component analysis and linear discriminant analysis methods to extract linear and nonlinear feature information from coal and gas outbursts influencing factors. Secondly, in order to realize the complementarity and correlation between coal and gas outbursts influencing factors, we perform parallel feature fusion to combine the extracted linear and nonlinear feature information. Thirdly, an improved classifier called BO–MKRVM has been proposed that combines mixed kernel relevance vector machine (MKRVM) and Bayesian optimization (BO) algorithm to predict coal and gas outbursts according to the extracted features. In BO–MKRVM model, an effective mixed kernel function which combines Gaussian kernel function and Sigmoid kernel function is proposed to improve the learning and generalization ability of the MKRVM classifier, then the BO and tenfold cross-validation are utilized to optimize kernel parameters and weight coefficients of MKRVM with strong global and local search capability, the proposed BO–MKRVM classifier is performed on coal and gas outbursts dataset. Compared with the single feature extraction method, the combination of linear and non-linear feature extraction methods can obtain complete feature information and contribute to the classification performance of outbursts. The mixed kernel function considers the characteristics of coal and gas outbursts sample data, which can also effectively improve the outbursts accuracy. After the MKRVM classifier is optimized by BO algorithm, the BO–MKRVM classifier has better fitting effect and generalization ability, and obtains higher accuracy with a lower time. The experimental results are obviously better than those of other classification models, which further verifies the applicability of the proposed coupled model.

Industrial hemp has gained resurgent interest recently for applications in various sectors. This study evaluated 11 different industrial hemp [6 fiber-only and 5 dual-purpose (fiber and grain)] cul...

Spatial variability is a natural attribute of soil properties and strongly affects seismic performance of earth structures. A novel stochastic dynamics method, probability density evolution...

Large-scale microalgae cultivation for biodiesel production is expected to be performed utilizing open air growth infrastructure that will inherently introduce ash into the system. High ash biomass represents a significant challenge for the production of biofuel as it increases processing capital and operational costs. This study assesses the economic viability of pretreatment to remove ash from biomass grown with an algal turf scrubber (ATS). An engineering process model of biofuel production was developed based on an ATS growth system followed by an ash removal process and conversion of the biomass to fuels through hydrothermal liquefaction. The model was validated with literature data for the growth and conversion processes and with experimental data for 14 de-ashing processes using water washing or alkaline extraction. The engineering process model was integrated with techno-economic modeling to investigate the impact of ash on biomass and fuel selling prices. Capital costs associated with biofuel conversion doubled as ash content increased from 0% to 70%, increasing fuel selling price by 21%. Integrating ash removal resulted in reduced conversion capital costs (14–42%) based on the reduction of total mass processed. However, only water washes scenarios at 25 °C and 50 °C were found to reduce overall fuel selling price, with alkaline extraction scenarios showing a significant increase. Operational expenses associated with alkaline extraction de-ashing including wastewater treatment, chemical costs, and heating the microalgae slurry were found to significantly increase the overall fuel selling price of the microalgae biofuel by 17–92% depending on the operational scenario.

A probabilistic slope stability analysis framework based on the Newmark permanent displacement method and probability density evolution theory is presented to quantify the coupling impact a...

Seismic fragility analysis is an efficient way to study the seismic behaviour and performance of structures under the excitation of earthquakes of varying intensity, and an essential part of the se...

Feedstock price and availability are key challenges for biorefinery development. Biomass blending has been suggested as a route to overcome these limitations. However, the impacts of feedstock blending on the uncertainty in hydrolyzed sugar yields remain unclear. This study quantifies the uncertainties in the sugar yields from hydrolysis of the blends of corn stover, switchgrass, and grass clippings by considering both feedstock compositional variation and model uncertainty. The results indicate that feedstock blending reduces the uncertainties in sugar yields and delivers feedstock of more uniform quality. A 60/35/5 blend of corn stover, switchgrass, and grass clippings on average achieves a glucose yield of 32.6 g/100 g of biomass, which is comparable to those of corn stover (33.3 g/100 g) and switchgrass (32.9 g/100 g), but drastically higher than that of grass clippings (21.7 g/100 g). This same blend also achieves the lowest variance in glucose yield (2.9 g/100 g) compared to corn stover (3.1 g/100 g...

An anchored pile structure is a type of retaining structure that is widely used in excavation support systems, water-front structures, slope stabilization, and landslide prevention. This structure has good performance because the anchor can limit the displacement and control the deflection of the pile head. Field observations of the performance of various retaining structures during many recent earthquakes have revealed that these structures behave particularly well. However, the dynamic responses and seismic performance of this type of retaining structure in slope stabilization have not been elucidated. In this study, a large-scale shaking table test was conducted to investigate the seismic behavior of a landslide reinforced by anchored pile structures. The acceleration field, anchor force, bending moment, lateral earth pressure along the pile, and permanent displacement of the slope and pile are presented and discussed to systematically determine the seismic responses, reinforcement, and failure mechanism of this retaining structure. The tests results reveal that a landslide reinforced by anchored pile structures achieved good seismic performance even under strong earthquakes. Additionally, some reasonable measures are proposed to improve the seismic performance of a slope reinforced by anchored pile structures. The results obtained by this study can provide a theoretical basis for the seismic performance assessment and design of anchored pile structures.

The seismic performance and stability analysis of slopes are important in predicating damage and mitigating potential losses in landslide-prone areas. Fragility functions can give results of slope performance assessment that are more comprehensive and richer. This study presents a procedure of constructing seismic fragility functions for slope stability analysis with various vulnerability states based on incremental dynamic analysis (IDA). IDA is a performance-based earthquake engineering analysis based on a series of dynamic time history analyses conducted for suitable multiple-scaled seismic records. IDA not only estimates the seismic demand and capacity of systems but also provides basic data for the estimation of fragility functions. Firstly, an ensemble of seismic records meeting the requirements of specific site conditions of a slope is selected to consider the randomness of ground motion. A series of seismic stability analyses of the slope are performed to obtain the dynamic safety factor time history of the slope. Each minimum safety factor and corresponding seismic intensity measure is then extracted to develop a set of IDA curves. On the basis of IDA results, analytical seismic fragility functions of a slope are developed considering the prescribed various vulnerability states of the slope in terms of the safety factor. The failure probabilities of exceeding different specific vulnerability states for a given intensity measure of the earthquake are finally obtained.

Summary Electrification is part of process intensification being explored by the chemical industry to improve energy efficiency and to reduce greenhouse-gas emission. Ethylene production, using electrochemical-facilitated non-oxidative ethane dehydrogenation, is an emerging, but promising, process to facilitate electrification of the ethylene industry and represents the most untapped opportunity in the chemical industry. Herein, we highlight the low-temperature electrochemical ethylene production using solid-oxide membrane reactors/stacks (LoTempLene) and elucidate the opportunity of using it in the electrification trend. Detailed process simulation was conducted using Aspen Plus software, based on state-of-the-art results for energy and cost analysis, aiming to better understand the practical implications of the LoTempLene process versus conventional steam cracking. We also provide our perspective on the key challenges and possible solutions for low-temperature electrochemical ethylene production.

Slopes should be regarded as stochastic dynamic systems when investigating the uncertainty of ground motions. In engineering, this involves the propagation and spatial evolution of physical quantities (e.g., acceleration) that can be assessed with some probability. More specifically, stochastic stability and amplification effects are important issues under random seismic inputs. In studying the above, a large-scale shaking-table test is carried out to investigate the slope seismic response under random earthquake ground motions, where 144 ground-motion samples are generated using a time-evolution power spectrum model. In this test, acceleration evolves in a way that its PDF changes with time and space. In the time domain, the PDF variability first increases and then decreases with the progression of the earthquake. In the spatial domain, the PDF variability increases upslope, indicating that the mean and standard deviation of amplification factors increase with elevation. Moreover, the stability of the upper part of the slope stochastic dynamic system is poor. Meanwhile, the de-amplification effect of the slope toe is identified under random seismic inputs. Finally, we discuss different amplification factors and consider applications of the research results in slope engineering.

Raman mapping, scanning Kelvin probe force microscopy (SKPFM), and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDS) were combined to investigate oxidized zirconium alloys. Raman provided spatially resolved phase composition and relative stress state. When coupled with SKPFM, phase composition was correlated to Volta potentials differences. The potential of tetragonal zirconia was lower than the metal zirconium, making the tetragonal phase favorable for reaction with diffusing species, thus hindering further oxidation of the relatively cathodic metal. This provides new insight to the theory of the tetragonal phase being an oxidation barrier.

This paper examines the efficacy of ionic liquid (IL) pretreatment on seven different commercially harvested biomass types: corn stover, miscanthus, pine, sorghum, sugarcane bagasse, switchgrass, and wheat straw in an effort to improve the production of renewable fuels and chemicals from biomass derived sugars. Initial experiments screened the pretreatment of lodgepole pine, a particularly recalcitrant biomass feedstock, with nine different imidazolium based ionic liquids. After screening, one hydrophilic and one hydrophobic ionic liquid was selected for pretreatment tests on six commercially harvested biomasses. Ultimately, the hydrophilic ionic liquid functioned better for biomass pretreatment than the hydrophobic ionic liquid. These results were then compared to a traditional dilute acid pretreatment to examine the relative effectiveness of ionic liquid pretreatment across a variety of biomass and ionic liquid types. Total theoretical sugar yields after IL pretreatment varied widely by IL and biomass type and ranged from 4.9 to 90.2%. Dilute acid pretreatment showed consistent sugar yields for herbaceous material (from 71.4 to 80.8%) but low yield for lodgepole pine (22.8%). Overall, ILs showed the potential to reach slightly higher sugar yields than dilute acid and were particularly effective for woody feedstocks. More importantly, the sugar release kinetics for IL pretreatment were three times faster than dilute acid and gave maximum sugar yields after about 24 hours. Additional characterization of IL treated materials included scanning electron microscopy (SEM), x-ray diffraction (XRD), and compositional analysis. SEM and XRD showed qualitative and quantitative reductions in cellulose crystallinity (respectively) that correlated well to improved sugar release during enzymatic hydrolysis for hydrophilic ionic liquids. However, reductions in crystallinity associated with hydrophobic ionic liquids resulted in lower sugar release during enzymatic hydrolysis. Compositional analysis generally showed increased sugars content for hydrophilic ILs and increased lignin content for hydrophobic ILs.