Computer Simulation Model Research Articles

Computational simulation model of transcatheter edge-to-edge mitral valve repair: a proof-of-concept study.

As transcatheter mitral valve (MV) interventions are expanding and more device types and sizes become available, a tool supporting operators in pre-procedural planning and the clinical decision-making process is highly desirable. We sought to develop a finite element computational simulation model to predict the results of transcatheter edge-to-edge repair (TEER) interventions. We prospectively enrolled patients with secondary mitral regurgitation (MR) referred for a clinically indicated TEER. The 3D trans-oesophageal echocardiograms performed at the beginning of the procedure were used to perform the simulation. On the 3D dynamic model of the MV that was first obtained, we simulated the clip implantation using the same clip type, size, number, and implantation location that was used during the intervention. The 3D model of the MV obtained after the simulation of the clip implantation was compared with the clinical results obtained at the end of the intervention. We analysed the degree and location of residual MR and the shape and area of the diastolic MV area. We performed computational simulation on five patients. Overall, the simulated models predicted well the degree and location of the residual regurgitant orifice(s) but tended to underestimate the diastolic mitral orifice area. In this proof-of-concept study, we present preliminary results on our algorithm simulating clip implantation in five patients with functional MR. We show promising results regarding the feasibility and accuracy in terms of predicting residual MR and the need to improve the estimation of the diastolic MV area.

Discrete Dynamic System Modeling for Simulated Moving Bed Processes

Although the simulated moving bed (SMB) process boasts advantages such as high productivity and low consumption, the cost of obtaining optimized parameters through practical experiments to control the separation process can be enormous due to its complex nonlinear characteristics. Consequently, the successful transformation of the SMB separation process into a mathematical dynamic model for computer simulation would greatly reduce the research costs associated with experimental studies. In this study, the Crank–Nicolson method was employed to discretize and dynamize the SMB process, enabling the simulation of processes under both linear and Langmuir isotherms. The results of the simulation experiments demonstrated the feasibility and high efficiency of this approach, thereby establishing a solid foundation for further advancements in online control strategies.

Simulating worm feeding patterns with computational models

Worms create complex paths when moving through sediment to feed. This research applies computer simulation models to provide a unique approach to visualise and quantify the process by which complex worm paths can emerge from simple local movement decisions. A grid environment is proposed in which worms can move with choice of up to 8 directions at each step. This uses a square grid with diagonal paths which has not been investigated before and the resulting number of complex paths is increased compared to triangular grids. Results identify many novel worm paths. Some of the resulting paths are symmetrical, others produce repetitive looping paths, others return to the origin. Interesting worm paths are identified with chaotic movement. Some include oscillating between chaotic and ordered movement for which the outcome is still unknown after millions of steps. A conclusion that may be extrapolated to other creatures is that local movement decisions of a species substantially determine the overall global search strategy that emerges.

Efficient fiber coupling system for simultaneous beam shaping and wavelength combining based on misaligned stepped prism multiplexing

Due to the substantial contrast in the output beam quality between the two directions of the semiconductor laser, efficiently coupling the beam directly into the fiber is difficult. In this study, an efficient shaping method based on step multiplexing of misaligned step prisms is proposed and investigated systematically. First, multiple laser stacks eliminate dark areas to improve the beam quality through the full utilization of the transmission and reflection surfaces of the misaligned stepped prisms, which also improves the efficiency of the stepped prisms. It also simultaneously realizes laser wavelength combining based on reflective surface multiplexing without affecting the quality of the beam on the premise of improving the output power. Finally, the whole beam shaping system is completed without using cut-transform-rearranging prisms. The method couples four groups of laser stacks into a single fiber with a fiber diameter of 400 µm and a numerical aperture of 0.22. It can be seen from the computer-simulated model outputs that the final fiber output power can reach 2255.4 W and that the system as a whole has a light-to-light translation rate of 88.1%.

Performance evaluation of multilevel multiphase inverters by piece-wised linearized simulation models

The paper deals with the design issue of the computer simulation models of the traction inverter reflecting request on the rapid investigation of the efficiency performance under various operational conditions. According to this, a piece-wised linearized simulation tool PLECS is selected for model development, which considers the relevant loss behaviour of the main power circuit semiconductor components. The topologies, for which the simulation models are created, are topologies, one of which is commonly used across the automotive industry as the heart of the traction drive (VSI – Voltage Source Inverter), and its perspective alternative three-level traction inverter topology T-NPC – T-type Neutral Point Clamped. The simulation models created in the given simulation tool are thus subjected to the analysis of power parameters, which also include the calculated power losses of the entire system of semiconductor devices for both topologies of the traction inverter. Based on the obtained power parameters, the efficiency performance under various operational conditions of both topologies is evaluated. The presented methodology enables rapid investigation of operational performance enabling fast optimization methods. Any design of linearized simulation models in the PLECS simulation tool, whose core consists of semiconductor elements, can be analyzed by the proposed methodology.

Numerical investigation of the flow noise of an underwater vehicle

Flow noise is an important issue of underwater vehicles. In this paper, the ability of different numerical methods to predict the flow noise of the DARPA SUBOFF underwater vehicle model is investigated and compared. It is found that the front of the command deck and the tail fins are the main noise sources. Numerical results show that delayed detached eddy simulation is a suitable computational model for flow noise simulations.

Conversion of a regular patient room to negative pressure at Ancona university hospital (Italy). A combined experimental and numerical investigation

Negative pressure isolation rooms are employed to prevent the spread of infectious diseases to surrounding spaces. This study reports a combined experimental and numerical analysis aimed at reliably assessing the performance of hospital ventilation systems and effectively reducing the risk of airborne infections. The study appraises the enhancement of the safety conditions by retrofitting an existing, positive pressure room ventilation system with a negative pressure and recirculation one. The assessment consisted in experimental measurements of airborne particle concentration and Computational Fluid Dynamics (CFD) simulations with Lagrangian particle tracking of respiratory droplets. The ventilation performance improvement was quantified in terms of recovery rate, contaminant removal effectiveness, particle transfer toward adjacent spaces and probability of infection.Two experimental campaigns were carried out: an ISO standard recovery assessment and a test in real operational conditions. The negative pressure configuration significantly improved the safety inside the patient ward: the recovery rate for droplets with diameter larger than 5 μm increased by a factor three, and the contaminant removal effectiveness after 15 min increased from 45% to 81%. The numerical model for Computational Fluid Dynamics simulation was successfully validated, confirming the ability of the approach to reproduce the undergoing Physics. The negative pressure design eliminated the particle transmission to surrounding spaces, while 2.5% of the emitted respiratory droplets escaped the room in the original existing scenario. The probability of infection after 15 min exposure was reduced by a factor three and peak values reaching 15% were limited to the immediate vicinity of the patients.

A Structure Independent Molecular Fragment Interfuse Model for Mesoscale Dissipative Particle Dynamics Simulation of Peptides.

There is a need to develop robust computational models for mesoscale simulation of the structure of peptides over large length scales toward the discovery of novel peptides for medical applications to address the issues of peptide aggregation, enzymatic degradation, and short half-life. The primary objective was to predict the structure and conformation of peptides whose native structures are not known. This work presents a new model for computation of interaction parameters between the beads in coarse-grained dissipative particle dynamics (DPD) simulation that is properly calibrated for amino acids, supports compressibility requirement of water molecules, and accounts for subtle differences in the structure of amino acids and the charge in the side chain of charged amino acids. This new model is referred to as Structure Independent Molecular Fragment Interfuse Model, abbreviated as SIMFIM, because it accounts for specific interactions between different beads, which represent molecular fragments of the amino acids, in calculating nonbonded interaction parameters in the absence of knowing the actual peptide structure. The electrostatic interactions are incorporated in this model by using a normal distribution of charges around the center of the beads to prevent the collapse of oppositely charged soft beads. The uniquely parameterized DPD force field in the SIMFIM model is optimized for a given peptide with respect to the degree of coarse-grained graining for simulating the peptide over long times and length scales. The SIMFIM model was tested in this work using four peptides, namely, TrpZip2, Rubrivinodin, Lihuanodin, and IC3-CB1/Gai peptides, whose structures were sourced from the Protein Data Bank. The SIMFIM model predicted radius of gyration (Rg) values for the peptides closer to the actual structures as compared to the conventional model, and there was less deviation between the predicted and actual structures of the peptides.

Theoretical considerations and empirical predictions of the pharmaco- and population dynamics of heteroresistance

Antibiotics are considered one of the most important contributions to clinical medicine in the last century. Due to the use and overuse of these drugs, there have been increasing frequencies of infections with resistant pathogens. One form of resistance, heteroresistance, is particularly problematic; pathogens appear sensitive to a drug by common susceptibility tests. However, upon exposure to the antibiotic, resistance rapidly ascends, and treatment fails. To quantitatively explore the processes contributing to the emergence and ascent of resistance during treatment and the waning of resistance following cessation of treatment, we develop two distinct mathematical and computer-simulation models of heteroresistance. In our analysis of the properties of these models, we consider the factors that determine the response to antibiotic-mediated selection. In one model, heteroresistance is progressive, with each resistant state sequentially generating a higher resistance level. In the other model, heteroresistance is non-progressive, with a susceptible population directly generating populations with different resistance levels. The conditions where resistance will ascend in the progressive model are narrower than those of the non-progressive model. The rates of reversion from the resistant to the sensitive states are critically dependent on the transition rates and the fitness cost of resistance. Our results demonstrate that the standard test used to identify heteroresistance is insufficient. The predictions of our models are consistent with empirical results. Our results demand a reevaluation of the definition and criteria employed to identify heteroresistance. We recommend that the definition of heteroresistance should include a consideration of the rate of return to susceptibility.

Abstract LB021: BAU-243: A novel BCL-2 inhibitor inducing autophagic cell death in glioblastoma, unveiled through multistep virtual screening, comprehensive in vitro and in vivo animal model evaluation

Abstract The excessive expression of antiapoptotic members in the B-cell leukemia/lymphoma-2 (BCL-2) family proteins emerges as a noteworthy oncogenic target in cancer cells. Employing a multistep virtual screening and filtering approach that integrates structure and ligand-based drug design, we aimed to identify novel and potent BCL-2 inhibitors from a sizable small molecule database, comprising over 210,000 compounds. Subsequently, seven selected molecules underwent rigorous biological activity tests in human cancer cell lines and Time-Resolved Fluorescence Resonance Energy Transfer (TR-FRET) assays. Four of these compounds exhibited notable inhibitory effects on cancer cell proliferation and led to an increase in apoptotic cell fractions. Among the identified compounds, BAU-243 displayed a substantial affinity for Bcl-2, demonstrating efficacy in reducing glioblastoma (GBM) cell proliferation, including cancer-initiating cells. Notably, in contrast to the selective Bcl-2 inhibitor ABT-199, BAU-243 induced autophagic cell death in GBM cells. In vivo investigations using orthotopic brain tumor models revealed a significant reduction in tumor growth with BAU-243 compared to both the vehicle group and animals treated with ABT-199. Computational modeling simulations, in concordance with in vitro findings, proposed that BAU-243 activates autophagic cell death by disrupting the Beclin 1:Bcl-2 complex. This positions BAU-243 as a promising small molecule for the treatment of GBM. Citation Format: Seyma Calis, Berna Dogan, Asuman Celebi, Ozlem Yapicier, Turker Kilic, Eda Tahir Turanli, Timucin Avsar, Serdar Durdagi. BAU-243: A novel BCL-2 inhibitor inducing autophagic cell death in glioblastoma, unveiled through multistep virtual screening, comprehensive in vitro and in vivo animal model evaluation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB021.

The influence of gene flow on population viability in an isolated urban caracal population.

Wildlife populations are becoming increasingly fragmented by anthropogenic development. Small and isolated populations often face an elevated risk of extinction, in part due to inbreeding depression. Here, we examine the genomic consequences of urbanization in a caracal (Caracal caracal) population that has become isolated in the Cape Peninsula region of the City of Cape Town, South Africa, and is thought to number ~50 individuals. We document low levels of migration into the population over the past ~75 years, with an estimated rate of 1.3 effective migrants per generation. As a consequence of this isolation and small population size, levels of inbreeding are elevated in the contemporary Cape Peninsula population (mean FROH = 0.20). Inbreeding primarily manifests as long runs of homozygosity >10 Mb, consistent with the effects of isolation due to the rapid recent growth of Cape Town. To explore how reduced migration and elevated inbreeding may impact future population dynamics, we parameterized an eco-evolutionary simulation model. We find that if migration rates do not change in the future, the population is expected to decline, though with a low projected risk of extinction. However, if migration rates decline or anthropogenic mortality rates increase, the potential risk of extinction is greatly elevated. To avert a population decline, we suggest that translocating migrants into the Cape Peninsula to initiate a genetic rescue may be warranted in the near future. Our analysis highlights the utility of genomic datasets coupled with computational simulation models for investigating the influence of gene flow on population viability.

Parametric analysis and optimization of the combustion process and pollutant performance for ammonia-diesel dual-fuel engines

As a low-cost, carbon-free, and widely available hydrogen carrier fuel, ammonia has now regained peoples’ attention in the future development of the carbon-neutral engine. To evaluate the feasibility of ammonia as a carbon-reducing fuel for a high-power diesel engine, a computational fluid dynamics simulation model of a Caterpillar 3401 diesel engine has been established and validated. Initially, an analysis was conducted to examine the effects of different ammonia energy fractions on combustion and the generation of emissions. Subsequently, to address issues related to incomplete ammonia combustion and a decline in engine power performance, a novel fuel injection strategy was developed. This strategy optimizes the distribution of diesel within the combustion chamber and the combustion process of ammonia-diesel dual-fuel by coordinating the injection timing of diesel fuel with the injection angle. The results indicate that an ammonia energy fraction of 40% is deemed to be an optimal mixing ratio for ammonia addition. Compared with pure diesel mode, greenhouse gas emissions are reduced by 34.3%, and the indicated mean effective pressure is only reduced by 4% when the ammonia energy fraction is 40%. Collaborative optimization of fuel injection timing and angle can achieve multi-point pilot ignition, shorten the combustion duration, and thus approach the effect of premixed combustion. This leads to a substantial decrease in unburned ammonia emissions, with the optimal unburned ammonia emission injection scheme registering only 0.279 g/kW·h, a mere 1.63% of the emissions under the original injection scheme with a 40% ammonia energy fraction. Additionally, the rapid combustion contributes to an increase in in-cylinder temperature, resulting in a significant reduction in N2O and CO emissions.

Terramechanics Models for Tracked Vehicle Terrain Interaction Analysis A Review

Efficient manoeuvrability of off-road tracked vehicles such as military tanks and rovers is essential in ensuring the success of military/extra-terrestrial operations. To achieve this, in-depth research on vehicle-terrain interaction is crucial. This manuscript deals with reviewing the ways to study terramechanics viz. theoretical, empirical, and field tests, and proposing the merits and demerits of each method. Under the theoretical approach, empirical, numerical, and semi-empirical methods are discussed. Under the empirical approach, the method based onthe vehicle cone index for tracked and wheeled vehicles is discussed. Under the numerical approach, advantages and disadvantages of Finite Element Method (FEM) and Discrete Element Method (DEM) are discussed. Semi-empirical method, based upon a combination of the best features of numerical and empirical approaches discusses terrain response to normal repetitive loads and shear repetitive loads for tracked as well as wheeled vehicles. Pressure sinkage relationship for terrains at various loading conditions and shear stress displacement relationship for different terrains obtained through penetration and shear tests are discussed to determine the vehicle’s mobility parameters under a semi-empirical approach. Further, the Super element model, multi-body simulation model, and ride and cornering vibration model are discussed under computer simulation models. A detailed review of various models customized towards tracked vehicle-terrain interaction discussed in this manuscript helps the authors set up a laboratory for terramechanics at DIAT. Preliminary analysis along with conceptual design of the experimental setup is also discussed. In a nutshell, this paper attempts to summarize the research that has been carried out in the field of tracked vehicle-terrain inter action comprising of VCI, MMP, FEM, DEM, Super element model, Multibody technique, and Semi-empirical methods helping the authors to establish a laboratory of terramechanics for their M. Tech. program on Armament and Combat Vehicles at DIAT Pune.

МІНІМІЗАЦІЯ МІЖКЛІТЬОВОГО НАТЯГУ НА БЕЗПЕРЕРВНИХ СТАНАХ ЗА ЯКІРНИМИ СТРУМАМИ ЕЛЕКТРОПРИВОДІВ ПРОКАТНИХ КЛІТЕЙ

In the conditions of continuous rolling of graded profiles with no or too little metal deflection between adjacent rolling cages, the most promising is tension regulation based on information about the armature currents of the main electric drives. The effectiveness of the method of minimizing the tension of graded rolled products based on information about the armature currents of the main electric drives was investigated. The method is based on the hypothesis of the constant ratio of the armature current of the drive of the next cage to the armature current of the drive of the previous cage in the free rolling mode. The method involves predicting the free-rolling current in rolling electric drives based on information about the free-rolling current in the electric drives of previous cages. The study is based on a complex model of the process of continuous bar rolling in four finishing cages of a small-grade mill with individual electric drives equipped with subordinate speed control systems. Given the fundamental impossibility of approbation of the proposed method by the methods of an industrial experiment, verification of its operability requires computer simulation modeling. The created computer model allows for adequate simulation of the operation of the control system in the conditions of rolling in a continuous group of cages with an accuracy that is sufficient for conclusions about the effectiveness of its operation. According to the results of the study of the control system by means of computer simulation, the effectiveness of its work was proven, in particular, the reduction of the specific tension in all intercell spaces of the finishing group of roll stands to an acceptable level of 10 N/mm2 and a significant narrowing of the range of changes in the width of the finished rolled product.

492 Novel BH3 Mimetic Bcl-2 Inhibitor Promotes Autophagic Cell Death and Reduces in Vivo Glioblastoma Tumor Growth

INTRODUCTION: Anti-apoptotic members of the Bcl-2 family proteins play central roles in the regulation of cell death in glioblastoma, the most malignant type of brain tumor. Despite the advances in GBM treatment, there is still an urgent need for new therapeutic approaches. METHODS: In silico studies resulted in 500,000 molecules being screened with computer-aided drug design methods and the molecule with the highest binding affinity was selected and named BAU-243. Cell viability, IC50 value, tumor formation potential, tumor spheroid formation potential, tumor invasion studies were investigated following BAU-243 application. The molecular changes caused by Bcl-2 inhibition were demonstrated by quantitative PCR, western blot and immunofluorescence methods. In in vivo studies, glioma tumors were transplanted intracranially into Nod Scid Gamma(NSG) mice using the mouse xenograft model. RESULTS: Here, we report a novel 4-thiazolidinone derivative BH3 mimetic, BAU-243 that binds to Bcl-2 with a high affinity. BAU-243 effectively reduced overall glioblastoma cell proliferation including a subpopulation of cancer-initiating cells in contrast to the selective Bcl-2 inhibitor ABT-199. While ABT-199 successfully induces apoptosis in high BCL2-expressing neuroblastoma SHSY-5Y cells, BAU-243 triggered autophagic cell death rather than apoptosis in A172 cells, indicated by the upregulation of BECN1, ATG5, and MAP1LC3B expression. Lc3b-II, a potent autophagy marker, was significantly upregulated following BAU-243 treatment. Moreover, BAU-243 significantly reduced tumor growth in vivo in orthotopic brain tumor models when compared to the vehicle group, and ABT-199 treated animals. To elucidate the molecular mechanisms of action of BAU-243, we performed computational modeling simulations that were consistent with in vitro results. CONCLUSIONS: Results indicated that BAU-243 activates autophagic cell death by disrupting Beclin 1:Bcl-2 complex, and may serve as a potential small molecule for the treatment of glioblastoma.

Abstract MP06: Cardiovascular Disease in Community-Dwelling US Adults Involved With the Criminal Justice System: A Simulation Analysis

Introduction: Approximately 4.4 million US adults live in the community while on probation or parole. They have disproportionately elevated cardiovascular risk factors, morbidity and mortality, along with limited access to healthcare. However, the long-term burden of cardiovascular disease (CVD) in this population is uncertain. We developed a simulation model to quantify cardiovascular risk and adverse events in community-dwelling US adults involved with the criminal justice system, leveraging all known sources of data on this under-studied, high-risk population. Methods: We adapted the CVD Policy Model, a validated state-transition simulation model of CVD in all US adults, using input data specific to 25-54 year-old individuals on probation or parole in 2018. Population size was defined using estimates from the Bureau of Justice Statistics. CVD risk factor burden was approximated by re-weighting data from the National Health and Nutrition Examination Survey years 2005 to 2018 to match demographic, socioeconomic, and health variables among individuals reporting past-year probation or parole in the National Survey on Drug Use and Health. CVD incidence and mortality rates were calibrated to outcomes in cohort studies and vital statistics data. Outcomes were myocardial infarction (MI), stroke, and death over a 10-year horizon (2018-2027) and were compared with projections for an age- and gender-matched cohort of adults in the general US population. We also examined projected reductions in CVD outcomes over 10 years that could be expected if risk factor distributions in the probation/parole population were similar to distributions observed for the general US population. Results: The simulated cohort consisted of 2.9 million adults 25-54 years of age on probation or parole in 2018; 71% were men, 30% were living below the poverty line, and 57% had no regular access to healthcare. An estimated 61% were current smokers, 29% had BP ≥130/80 mmHg, and 8% had diabetes. The study cohort was projected to experience between 36,400 and 69,600 incident MIs and between 22,400 and 37,500 incident strokes over 10 years. This would be 1.4-2.6 times the CVD incidence in age- and gender-matched adults in the general US population. Lowering rates of active smoking in those on probation or parole to rates observed for the general US population (i.e., from 61% to 21%) would reduce MI and stroke events by 16,400 to 29,100 over 10 years, a 27% reduction from current projections. Discussion: We developed and calibrated a computer simulation model to quantify the burden of CVD in community-dwelling US adults followed by the US justice system. We project that adults on probation or parole have higher CVD risk than the general US population. Future work will leverage this platform to estimate the impact of clinical, community, and policy interventions to reduce CVD burden in this vulnerable population.

Abstract 60: Cost-Effectiveness of Intensive Lipid-Lowering in Young Adulthood

Introduction: Cumulative exposure to elevated low-density lipoprotein cholesterol (LDL-C) in young adulthood (ages 18-39) increases later life atherosclerotic cardiovascular disease risk. Statins are cost-effective in young adults with LDL-C ≥130 mg/dL. However, current guidelines only recommend statins for LDL-C ≥190 mg/dL. Some young adults may not achieve treatment goals with statin monotherapy and additional lipid-lowering therapy may be cost-effective, especially given the advent of generic pricing for ezetimibe and reduced pricing for PCSK9 inhibitors (PCSK9-Is). Objective: We aimed to estimate the cost-effectiveness of statins with supplemental ezetimibe and supplemental PCSK9-Is in US young adults with LDL-C ≥130 mg/dL. Methods: The CVD Policy Model, an established computer simulation model, calculated the lifetime costs and quality-adjusted life years (QALYs) of lipid-lowering therapy. Analyses were stratified by pretreatment LDL-C and sex and the model accounted for cumulative LDL-C exposure in young adulthood. Treatment costs and effects were derived from published literature and publicly available data. Results were presented as incremental cost-effectiveness ratios (ICERs) and categorized as highly cost-effective (<$50,000/QALY), intermediately cost-effective ($50,000-$150,000/QALY), and not cost-effective (>$150,000/QALY). Results: Compared with no treatment, statin plus ezetimibe therapy was highly cost-effective for young adult men with LDL-C ≥160 mg/dL (ICER: $38,400/QALY; Table) and young adult women with LDL-C ≥190 mg/dL (ICER: $26,600/QALY). Statin plus PCSK9-I therapy substantially increased QALYs but was not cost-effective in any subgroup. To be highly cost-effective for young adults with LDL-C ≥190 mg/dL, PCSK9-I prices would need to be reduced by 61%. Conclusion: With generic pricing, statin plus ezetimibe therapy is highly cost-effective for young adults with elevated LDL-C. Large price reductions are required for statins plus PCSK9-Is to be cost-effective.

MELCOR – DAKOTA coupling for uncertainty analyses in the SNAP environment/architecture

Uncertainty estimation to assess figures of merit characterizing evolution of a severe accident transient is a topic of current investigation in development of best-estimate plus uncertainty methodology. The probabilistic method to propagate input uncertainty is one of the methodologies used to develop Uncertainty Analyses (UAs). Using this methodology, UAs are performed by sampling probability distributions that describe the range of possible values that computer simulation model inputs can have. For each sample (or realization) of a set of uncertain input parameters, a computer simulation is performed. From the range of code simulation results obtained for each input realization, a distribution of code results is obtained. In this process, the distribution of input uncertainties is propagated to obtain a distribution of possible code results (i.e., the code output uncertainty). This probabilistic methodology is facilitated using Uncertainty Tools (UTs), which can be coupled with the accident analysis computer code to perform an UA. One of the UTs currently available is DAKOTA, developed by Sandia National Laboratories. DAKOTA is also provided as a SNAP plug-in. SNAP is a graphical user interface designed to support the use of USNRC codes (MELCOR, TRACE, etc). This paper is entirely derived from the NUREG/IA-532 issued by USNRC in April 2023 (Mascari et al., 2023) and has as a major target to summarize the main needs of UA in severe accident, the main element of the probabilistic method to propagate input uncertainty, and the workflow within SNAP to assist other interested analysts with their applications given they are members of the USNRC Cooperative Severe Accident Research Program (CSARP).

Mesoscale model for computational simulation of reaction driven by dielectric breakdown in metal-polymer propellants

The reactivity of heterogeneous energetic materials (HEMs) intimately depends on the underlying microstructural effects. For reactive materials, key factors include the microstructure distribution, morphology, size scale of heterogeneities, reactant mixing, and chemical kinetics of the reactants. We report the development of a mesoscale model for simulating the evolutions of the hotspot field and associated reaction processes when such materials are exposed to external excitations. The model explicitly accounts for microstructure, interdiffusion between the reactant species, advection of the species mixture, and chemical kinetics of the reaction. An Arrhenius relation is used to capture the rate of reactive heat release. The particular material analyzed is a composite of poly(vinylidene fluoride-co-trifluoroethylene) and nanoaluminum [or P(VDF-TrFE)/nAl]. The excitation leading to the initial microstructural temperature increase that kicks off the exothermic reactive processes is the dissipative heating arising from dielectric breakdown under the electric field developed through piezoelectricity and flexoelectricity of P(VDF-TrFE). As such, the model resolves both the breakdown process and the diffusion, advection, and exothermic reaction processes. The evolutions of the temperature and species distribution fields under the combined effects of breakdown and chemistry are used to predict the effects of microstructure, diffusion, and kinetics on several key metrics characterizing the reactive responses of the material. This mesoscale framework admits the quantification of uncertainties in these predicted macroscopic behavior measures due to microstructure heterogeneity fluctuations through the use of multiple, random but statistically equivalent microstructure instantiations. Although the particular hotspot inducing mechanism considered is dielectric breakdown here, the framework can be adapted to analyze reaction initiation and propagation and establish microstructure–reaction behavior relations under other types of hotspot inducing mechanisms, such as thermomechanical inelastic dissipation, frictional heating, and laser or microwave excitation.

Can computer simulation support strategic service planning? Modelling a large integrated mental health system on recovery from COVID-19

BackgroundCOVID-19 has had a significant impact on people’s mental health and mental health services. During the first year of the pandemic, existing demand was not fully met while new demand was generated, resulting in large numbers of people requiring support. To support mental health services to recover without being overwhelmed, it was important to know where services will experience increased pressure, and what strategies could be implemented to mitigate this.MethodsWe implemented a computer simulation model of patient flow through an integrated mental health service in Southwest England covering General Practice (GP), community-based ‘talking therapies’ (IAPT), acute hospital care, and specialist care settings. The model was calibrated on data from 1 April 2019 to 1 April 2021. Model parameters included patient demand, service-level length of stay, and probabilities of transitioning to other care settings. We used the model to compare ‘do nothing’ (baseline) scenarios to ‘what if’ (mitigation) scenarios, including increasing capacity and reducing length of stay, for two future demand trajectories from 1 April 2021 onwards.ResultsThe results from the simulation model suggest that, without mitigation, the impact of COVID-19 will be an increase in pressure on GP and specialist community based services by 50% and 50–100% respectively. Simulating the impact of possible mitigation strategies, results show that increasing capacity in lower-acuity services, such as GP, causes a shift in demand to other parts of the mental health system while decreasing length of stay in higher acuity services is insufficient to mitigate the impact of increased demand.ConclusionIn capturing the interrelation of patient flow related dynamics between various mental health care settings, we demonstrate the value of computer simulation for assessing the impact of interventions on system flow.