Search

• The Coastal Generalized Ecosystem Model (CGEM) is an open-source model. • CGEM offers different formulations for rate processes, providing a flexible model structure. • Model formulations have significant effects on simulation outcomes. • Flexible model structure is important for adapting models to different ecosystems. • Formulations impact simulation outcomes for climate change and HABs. The Coastal Generalized Ecosystem Model (CGEM) is a biogeochemical model developed to study regulating processes of water-column optical properties, water-column and benthic carbon, oxygen, and nutrient cycles, and phytoplankton and zooplankton dynamics. CGEM offers numerous formulations for important rate processes, providing users flexibility in altering model structure. This flexibility also provides a means for evaluating model structural uncertainty and impacts on simulations, which are rarely evaluated with numerical ecosystem models. As an open-source model, CGEM also offers users the option to implement new formulations or modify existing routines. We also provide a full description of the model formulations, state variables, and model parameters in CGEM. Using two published case studies, we explore how different formulations for light attenuation, phytoplankton temperature growth response, and sediment processes impact simulations. We discuss CGEM's role as a new ecosystem model within the modeling community and opportunities to address current and future water quality issues. [ABSTRACT FROM AUTHOR]

This paper aims to explore the optimal control of the novel pandemic COVID-19 using non-clinical approach. We formulate a mathematical model to analyze the transmission of the infection through different human compartments. By applying a sensitivity test, we obtain the sensitivity indexes of the parameters involved in the transmission of the disease. We demonstrate the most active/sensitive parameters to analyze the spread of the coronavirus COVID-19. The most active transmission parameters are interposed by introducing control variables. The control intervention is in the form of smart lockdown, frequent handwash, control of the disease's side effects, face mask, and sanitizer. We Formulate Hamilton and Lagrangian to investigate the existence of the optimal control. Pontryagin's Maximum Principle describes the control variables in the optimal control model. The objective function is designed to reduce both the infection and the cost of interventions. We use numerical simulation to verify the results of the control variables by Matlab 2019. [ABSTRACT FROM AUTHOR]

Summary The thermodynamically constrained averaging theory (TCAT) is used to formulate a modeling framework for mechanistic models of species transport in multiphase porous medium systems containing two fluid phases and a solid phase. Primary restrictions guide the selection of entities and the set of conservation and balance equations needed to formulate an augmented entropy inequality (EI). Classical irreversible thermodynamics is upscaled from the microscale to the macroscale and used to provide a connection among material derivatives that arise from the conservation and balance equations under near-equilibrium conditions. An essentially exact constrained EI (CEI) is derived to approach the force-flux form of the EI that is desired. A set of approximations is applied to the CEI to produce a non-unique simplified EI (SEI), which is in the strict force-flux form needed to guide the formulation of closure relations. Sets of secondary restrictions are applied to the general SEI to form simpler subsets of the general SEI that apply for the local thermal equilibrium and isothermal cases. The SEI is then used to constrain the permissible form of the closure relations and to formulate a set of low-order closure relations. A specific model instance is formulated in closed form by specifying a complete set of conservation equations and closure relations. Many other model instances can be derived from the general modeling framework presented, and these potential extensions are discussed. [ABSTRACT FROM AUTHOR]

Abstract: This work is the ninth in a series of papers on the thermodynamically constrained averaging theory (TCAT) approach for modeling flow and transport phenomena in multiscale porous medium systems. A fundamental approach is developed to model the transition region between a two-fluid-phase porous medium system and a single-fluid-phase system, including species transport. A general model formulation is developed along with an entropy inequality to guide the specification of closure relations. The general model formulation and entropy inequality are then used to specify a closed system. The transition region model developed in this work is a generalization and extension of coupling conditions commonly used in sharp interface models. The theoretical framework has multiple areas of potential applicability including terrestrial-atmospheric contact zones, surface water-sediment interface zones, and industrial drying processes. [Copyright &y& Elsevier]

Abstract: Models formulated to associate odors and odorants in many industrial and agricultural fields ignore the potential effect of relative humidity on odor perception, and are not validated. This study addresses literature limitations by formulating a model that includes relative humidity and by validating the model. The model employs measured paired values, n = 102, of indoor odors and odorants from freshly dewatered biosolids in a post-digestion dewatering building of a Water Reclamation Plant (WRP). A random sub-sample of n = 32 is used to validate the model by associating predicted vs. measured values (R 2 = 0.90). The model is validated again with a smaller independent database from a second WRP (R 2 = 0.85). Moreover this study asserts that reduction of hydrogen sulfide concentrations, conventionally used as a surrogate of sewage odors, to acceptable levels does not assure acceptable odor levels. It is concluded that: (1) The addition of relative humidity results in a stronger association between odors and odorants than the use of H2S alone; (2) the two step model validation indicates that the model is not simply site-specific but can be applied to similar facilities; and (3) the model is a promising tool for designing odor and odorant control strategies, the ultimate goal of engineering studies. [Copyright &y& Elsevier]

The ‘ODD’ (Overview, Design concepts, and Details) protocol was published in 2006 to standardize the published descriptions of individual-based and agent-based models (ABMs). The primary objectives of ODD are to make model descriptions more understandable and complete, thereby making ABMs less subject to criticism for being irreproducible. We have systematically evaluated existing uses of the ODD protocol and identified, as expected, parts of ODD needing improvement and clarification. Accordingly, we revise the definition of ODD to clarify aspects of the original version and thereby facilitate future standardization of ABM descriptions. We discuss frequently raised critiques in ODD but also two emerging, and unanticipated, benefits: ODD improves the rigorous formulation of models and helps make the theoretical foundations of large models more visible. Although the protocol was designed for ABMs, it can help with documenting any large, complex model, alleviating some general objections against such models. [Copyright &y& Elsevier]

Abstract: Transfer learning is the ability to apply previously learned knowledge to new problems or domains. In qualitative reasoning, model formulation is the process of moving from the unruly, broad set of concepts used in everyday life to a concise, formal vocabulary of abstractions, assumptions, causal relationships, and models that support problem-solving. Approaching transfer learning from a model formulation perspective, we found that analogy with examples can be used to learn how to solve AP Physics style problems. We call this process analogical model formulation and implement it in the Companion cognitive architecture. A Companion begins with some basic mathematical skills, a broad common sense ontology, and some qualitative mechanics, but no equations. The Companion uses worked solutions, explanations of example problems at the level of detail appearing in textbooks, to learn what equations are relevant, how to use them, and the assumptions necessary to solve physics problems. We present an experiment, conducted by the Educational Testing Service, demonstrating that analogical model formulation enables a Companion to learn to solve AP Physics style problems. Across six different variations of relationships between base and target problems, or transfer levels, a Companion exhibited a 63% improvement in initial performance. While already a significant result, we describe an in-depth analysis of this experiment to pinpoint the causes of failures. Interestingly, the sources of failures were primarily due to errors in the externally generated problem and worked solution representations as well as some domain-specific problem-solving strategies, not analogical model formulation. To verify this, we describe a second experiment which was performed after fixing these problems. In this second experiment, a Companion achieved a 95.8% improvement in initial performance due to transfer, which is nearly perfect. We know of no other problem-solving experiments which demonstrate performance of analogical learning over systematic variations of relationships between problems at this scale. [Copyright &y& Elsevier]

Abstract: This paper introduces a new model for disease outbreaks. This model describes the disease evolution through a system of nonlinear differential equations with distributed-delay. The main difference between classical SIR-model resides in the fact that the recovery rate of the population is expressed as a distributed-delay term modeling the time spent being sick by infected people. This model is identified to fit realistic measurements which shows the effectiveness of the model. Finally, we develop an optimal campaign vaccination strategy based on recent results on the impulsive control of time-delay systems. [Copyright &y& Elsevier]

Abstract: This work is the seventh in a series that introduces and employs the thermodynamically constrained averaging theory (TCAT) for modeling flow and transport in multiscale porous medium systems. This paper expands the previous analyses in the series by developing models at a scale where spatial variations within the system are not considered. Thus the time variation of variables averaged over the entire system is modeled in relation to fluxes at the boundary of the system. This implementation of TCAT makes use of conservation equations for mass, momentum, and energy as well as an entropy balance. Additionally, classical irreversible thermodynamics is assumed to hold at the microscale and is averaged to the megascale, or system scale. The fact that the local equilibrium assumption does not apply at the megascale points to the importance of obtaining closure relations that account for the large-scale manifestation of small-scale variations. Example applications built on this foundation are suggested to stimulate future work. [Copyright &y& Elsevier]

Abstract: This work is the sixth in a series of papers on the thermodynamically constrained averaging theory (TCAT) approach for modeling flow and transport phenomena in multiscale porous medium systems. Building upon the general TCAT framework and the mathematical foundation presented in previous works, the limiting case of connected two-fluid-phase flow is considered. A constrained entropy inequality is developed based upon a set of primary restrictions. Formal approximations are introduced to deduce a general simplified entropy inequality (SEI). The SEI is used along with secondary restrictions and closure approximations consistent with the SEI to produce a general functional form of a two-phase-flow model. The general model is in turn simplified to yield a hierarchy of models by neglecting common curves and by neglecting both common curves and interfaces. The simplest case considered corresponds to a traditional two-phase-flow model. The more sophisticated models including interfaces and common curves are more physically realistic than traditional models. All models in the hierarchy are posed in terms of precisely defined variables that allow for a rigorous connection with the microscale. The explicit nature of the restrictions and approximations used in developing this hierarchy of models provides a clear means to both understand the limitations of traditional models and to build upon this work to produce more realistic models. [Copyright &y& Elsevier]

Abstract: This work is the fifth in a series of papers on the thermodynamically constrained averaging theory (TCAT) approach for modeling flow and transport phenomena in multiscale porous medium systems. The general TCAT framework and the mathematical foundation presented in previous works are used to develop models that describe species transport and single-fluid-phase flow through a porous medium system in varying physical regimes. Classical irreversible thermodynamics formulations for species in fluids, solids, and interfaces are developed. Two different approaches are presented, one that makes use of a momentum equation for each entity along with constitutive relations for species diffusion and dispersion, and a second approach that makes use of a momentum equation for each species in an entity. The alternative models are developed by relying upon different approaches to constrain an entropy inequality using mass, momentum, and energy conservation equations. The resultant constrained entropy inequality is simplified and used to guide the development of closed models. Specific instances of dilute and non-dilute systems are examined and compared to alternative formulation approaches. [Copyright &y& Elsevier]

Abstract: This work is the fourth in a series of papers on the thermodynamically constrained averaging theory (TCAT) approach for modeling flow and transport phenomena in multiscale porous medium systems. The general TCAT framework and the mathematical foundation presented in previous works are built upon by formulating macroscale models for conservation of mass, momentum, and energy, and the balance of entropy for a species in a phase volume, interface, and common curve. In addition, classical irreversible thermodynamic relations for species in entities are averaged from the microscale to the macroscale. Finally, we comment on alternative approaches that can be used to connect species and entity conservation equations to a constrained system entropy inequality, which is a key component of the TCAT approach. The formulations detailed in this work can be built upon to develop models for species transport and reactions in a variety of multiphase systems. [Copyright &y& Elsevier]

Abstract: Analysis of longitudinal, spatial and epidemiological data often requires modelling dispersions and dependence among the measurements. Moreover, data involving counts or proportions usually exhibit greater variation than would be predicted by the Poisson and binomial models. We propose a strategy for the joint modelling of mean, dispersion and correlation matrix of nonnormal multivariate correlated data. The parameter estimation for dispersions and correlations is based on the Whittle’s [P. Whittle, Gaussian estimation in stationary time series, Bull Inst. Statist. Inst. 39 (1962) 105-129.] Gaussian likelihood of the partially standardized data which eliminates the mean parameters. The model formulation for the dispersions and correlations relies on a recent unconstrained parameterization of covariance matrices and a graphical method [M. Pourahmadi, Joint mean–covariance models with applications to longitudinal data: unconstrained parameterization, Biometrika 86 (1999) 677–690] similar to the correlogram in time series analysis. We show that the estimating equations for the regression and dependence parameters derived from a modified Gaussian likelihood (involving two distinct covariance matrices) are broad enough to include generalized estimating equations and its many recent extensions and improvements. The results are illustrated using two datasets. [Copyright &y& Elsevier]

Chemical engineers are turning to multiscale modelling to extend traditional modelling approaches into new application areas and to achieve higher levels of detail and accuracy. There is, however, little advice available on the best strategy to use in constructing a multiscale model. This paper presents a starting point for the systematic analysis of multiscale models by defining several integrating frameworks for linking models at different scales. It briefly explores how the nature of the information flow between the models at the different scales is influenced by the choice of framework, and presents some restrictions on model—framework compatibility. The concepts are illustrated with reference to the modelling of a catalytic packed bed reactor. [Copyright &y& Elsevier]

In the context of controlling the attitude of a rigid body, this communique uses recent results on representations of torques (moments) to establish cost functions. The resulting cost functions are both properly invariant under whatever choice of Euler angles is used to parameterize the rotation of the rigid body and have transparent physical interpretations. The function is related to existing works in geometric control theory and applications of optimal control theory to biomechanical systems. [ABSTRACT FROM AUTHOR]

Abstract: This short note proposes two model reformulations to improve the Hougen–Watson mathematical form of kinetic models and validate them on a typical heterogeneous kinetic problem. [Copyright &y& Elsevier]

• Proposed a rigorous formulation for gas hydrate formation and growth. • Addressed several practically relevant issues of porous media and saltwater. • Validated with data generated in reservoir mimicking environment at south China sea. • Observed a promising performance at the wide range of conditions. A potential source of energy is encapsulated in the form of natural gas hydrates found in the diverse permafrost and marine geological settings. To understand the hydrate dynamics, we articulate a rigorous mathematical formulation by contemplating the pervasive role of indigenous elements, including porous material and saline water of the natural gas hydrate reservoirs. This formulation takes into account the characteristic behavior of the porous media in the aspects of their porosity and particle size distribution, and the dynamic contribution of the saline water towards the hydrate formation and growth in reservoir mimicking environment. All relevant model parameters are tuned by using the generalized reduced gradient nonlinear optimization technique. The model is employed to investigate the dynamics of methane hydrate at diverse field conditions (e.g. porous medium with varying sizes of clay, sand and silt particles, amount of saline water, and operating pressure and temperature). Validating the model with experimental data for three different setups, its performance improvement is quantified in terms of the absolute average relative deviation (AARD). This proposed model shows a promising performance at the wide range of conditions. [ABSTRACT FROM AUTHOR]