Computer Simulation Model Research Articles

Virtual and Augmented Reality in the Disaster Management Technology: A Literature Review of the Past 11 years

This study presents a systematic review of the literature on virtual reality (VR), augmented reality (AR) and Mixed Reality (MR) used in disaster management. We consider the factors such as publication type, publication year, application domain, and technology used. We surveyed papers from 2009 to 2019 available in the Web of Science and Google Scholar database, and 84 research articles were selected for the review study. After an extensive review of the literature, it was found that the XR technology is applied extensively in computer simulation modeling, interaction techniques, training, infrastructure assessment and reconnaissance, and public awareness areas of disaster management. We found diverse advantages, opportunities, and challenges of XR usage for disaster management, which are discussed in detail. Furthermore, current research gaps in the field of XR technology for disaster management technology, which are needed to better support disaster management, are identified and discussed in an effort to provide direction to the future research.

Structural Optimization of Heat Sink for Thermoelectric Conversion Unit in Personal Comfort System

Based on the research background of improving personal thermal comfort and promoting building energy efficiency, personal comfort systems (PCSs) have recently received considerable attention. The thermoelectric conversion unit (TECU) has great potential in PCSs as it is compact in size, environmentally friendly and highly reliable. Aiming to improve heat exchange efficiency, this paper investigates the structural optimization of heat sink for the TECU used in PCSs. Firstly, the heat exchange mechanism of the thermoelectric module is analyzed. The structural design of the cold-side heat sink in the TECU is summarized as a multiobjective optimization problem in which four structural parameters (number of fin rows, fin thickness, fin height and thickness of base) of the heat sink are selected as the adjusting variables. Then, based on the establishment of the cold-side computational fluid dynamics simulation model, a multiobjective genetic algorithm is utilized for the optimization task. Sensitivity analysis demonstrates that the number of rows and the fin thickness have significant influence on the optimization objectives. Taking both the outlet airflow temperature and the velocity into consideration, five representative heat sinks involving two different materials are customized. A testing platform is built for performance comparison. Results show that the proposed optimization method can effectively improve the heat exchange efficiency of a TECU, which provides a reference for the TECU-based PCS design.

Acceptance sampling to aid in the verification of computational simulations

Advances in computing allow for the construction of increasingly large and complex models and simulations. Exhaustive error checking of these intricate, large computational simulation models is daunting and potentially impractical. This paper explores an approach to error-checking simulation model components using an Acceptance Sampling methodology from the field of industrial manufacturing. We propose a systematic process in which a simulation inspector examines only a fraction of the computational model elements to measure the errors present. Our proposed process could support established verification processes by sampling the simulation components to identify whether the model is acceptably error free and which components require correcting. The proposed methodology relies on several statistical constraints but serves the interests of simulation professionals as part of the overall verification process. We illustrate the application and usefulness of our methodology through a real-world case study of a citywide microscopic transportation model.

In Vivo Validation of a Cardiovascular Simulation Model in Pigs

Many computer simulation models of the cardiovascular system, of varying complexity and objectives, have been proposed in physiological science. Every model needs to be parameterized and evaluated individually. We conducted a porcine animal model to parameterize and evaluate a computer simulation model, recently proposed by our group. The results of an animal model, on thirteen healthy pigs, were used to generate consistent parameterization data for the full heart computer simulation model. To evaluate the simulation model, differences between the resulting simulation output and original animal data were analysed. The input parameters of the animal model, used to individualize the computer simulation, showed high interindividual variability (range of coefficient of variation: 10.1–84.5%), which was well-reflected by the resulting haemodynamic output parameters of the simulation (range of coefficient of variation: 12.6–45.7%). The overall bias between the animal and simulation model was low (mean: −3.24%, range: from −26.5 to 20.1%). The simulation model used in this study was able to adapt to the high physiological variability in the animal model. Possible reasons for the remaining differences between the animal and simulation model might be a static measurement error, unconsidered inaccuracies within the model, or unconsidered physiological interactions.

Modeling Chronic Kidney Disease in Type2 Diabetes Mellitus: A Systematic Literature Review of Models, Data Sources, and Derivation Cohorts.

IntroductionAs novel therapies for chronic kidney disease (CKD) in type 2 diabetes mellitus (T2DM) become available, their long-term benefits should be evaluated using CKD progression models. Existing models offer different modeling approaches that could be reused, but it may be challenging for modelers to assess commonalities and differences between the many available models. Additionally, the data and underlying population characteristics informing model parameters may not always be evident. Therefore, this study reviewed and summarized existing modeling approaches and data sources for CKD in T2DM, as a reference for future model development.MethodsThis systematic literature review included computer simulation models of CKD in T2DM populations. Searches were implemented in PubMed (including MEDLINE), Embase, and the Cochrane Library, up to October 2021. Models were classified as cohort state-transition models (cSTM) or individual patient simulation (IPS) models. Information was extracted on modeled kidney disease states, risk equations for CKD, data sources, and baseline characteristics of derivation cohorts in primary data sources.ResultsThe review identified 49 models (21 IPS, 28 cSTM). A five-state structure was standard among state-transition models, comprising one kidney disease-free state, three kidney disease states [frequently including albuminuria and end-stage kidney disease (ESKD)], and one death state. Five models captured CKD regression and three included cardiovascular disease (CVD). Risk equations most commonly predicted albuminuria and ESKD incidence, while the most predicted CKD sequelae were mortality and CVD. Most data sources were well-established registries, cohort studies, and clinical trials often initiated decades ago in predominantly White populations in high-income countries. Some recent models were developed from country-specific data, particularly for Asian countries, or from clinical outcomes trials.ConclusionModeling CKD in T2DM is an active research area, with a trend towards IPS models developed from non-Western data and single data sources, primarily recent outcomes trials of novel renoprotective treatments.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13300-022-01208-0.

Machine learning-based optimal design of groundwater pollution monitoring network

It is an important task of environmental management to design groundwater pollution monitoring network (GPMN) to find out the occurrence of pollution events and carry out remediation in time. However, there are many uncertain factors in the process of designing GPMN, which affect the GPMN design result. In the process of applying the Monte Carlo method for uncertainty analysis, groundwater numerical simulation model may be utilized thousands of times, which results in a huge computational load. In order to overcome this disadvantage, a machine learning (ML)-based surrogate model is constructed with Kriging method, to replace the computational simulation model under uncertainty of pollution sources and parameters. The 0–1 integer programming optimization model is constructed to maximally cover serious polluted area to detect the occurrence of groundwater pollution in time. The optimal design framework of GPMN based on proposed ML algorithm was applied in a domestic landfill in Baicheng City, China. The results showed that the ML-based surrogate model has a great fitness with the groundwater solute transport simulation model. The optimal results of GPMN indicated that monitoring wells should be mainly placed at the downstream of the leachate equalization basin. If more wells are allowed to be placed, part of wells could be placed at the downstream of the landfill. Moreover, the area where the pollution plumes of landfill site meet that of leachate equalization basin should be set as the key monitoring objective. Verification and comparison showed that the pollutant detection rate of the optimal layout scheme is far higher than random layout schemes, which proves the reliability of the ML-based optimal design scheme of GPMN.

Beyond 10-Year Risk: A Cost-Effectiveness Analysis of Statins for the Primary Prevention of Cardiovascular Disease.

Background:Cholesterol guidelines typically prioritize primary prevention statin therapy on the basis of 10-year risk of cardiovascular disease. The advent of generic pricing may justify expansion of statin eligibility. Moreover, 10-year risk may not be the optimal approach for statin prioritization. We estimated the cost-effectiveness of expanding preventive statin eligibility and evaluated novel approaches to prioritization from a Scottish health sector perspective.Methods:A computer simulation model predicted long-term health and cost outcomes in Scottish adults ≥40 years of age. Epidemiologic analysis was completed using the Scottish Heart Health Extended Cohort, Scottish Morbidity Records, and National Records of Scotland. A simulation cohort was constructed with data from the Scottish Health Survey 2011 and contemporary population estimates. Treatment and cost inputs were derived from published literature and health service cost data. The main outcome measure was the lifetime incremental cost-effectiveness ratio, evaluated as cost (2020 GBP) per quality-adjusted life-year (QALY) gained. Three approaches to statin prioritization were analyzed: 10-year risk scoring using the ASSIGN score, age-stratified risk thresholds to increase treatment rates in younger individuals, and absolute risk reduction (ARR)–guided therapy to increase treatment rates in individuals with elevated cholesterol levels. For each approach, 2 policies were considered: treating the same number of individuals as those with an ASSIGN score ≥20% (age-stratified risk threshold 20, ARR 20) and treating the same number of individuals as those with an ASSIGN score ≥10% (age-stratified risk threshold 10, ARR 10).Results:Compared with an ASSIGN score ≥20%, reducing the risk threshold for statin initiation to 10% expanded eligibility from 804 000 (32% of adults ≥40 years of age without CVD) to 1 445 500 individuals (58%). This policy would be cost-effective (incremental cost-effectiveness ratio, £12 300/QALY [95% CI, £7690/QALY–£26 500/QALY]). Incremental to an ASSIGN score ≥20%, ARR 20 produced ≈8800 QALYs and was cost-effective (£7050/QALY [95% CI, £4560/QALY–£10 700/QALY]). Incremental to an ASSIGN score ≥10%, ARR 10 produced ≈7950 QALYs and was cost-effective (£11 700/QALY [95% CI, £9250/QALY–£16 900/QALY]). Both age-stratified risk threshold strategies were dominated (ie, more expensive and less effective than alternative treatment strategies).Conclusions:Generic pricing has rendered preventive statin therapy cost-effective for many adults. ARR–guided therapy is more effective than 10-year risk scoring and is cost-effective.

Computer Simulation Model for Surface Generation in Turning process. (Dept. M(Production))

Computer Simulation Model for Surface Generation in Turning process. (Dept. M(Production))

SG-ACCORD: Designing Virtual Agents for Soft Skills Training in the School Context

This study focuses on the behavior of interactive agents and how to ground their implementation in psychology and cognitive modeling to capture fundamental psycho-pedagogical elements to deliver an effective competency-based training and assessment tool for teachers, trainers, and educators working in the school context. The study describes the design and implementation of a Serious Game, “Attain Cultural Integration through COnflict Resolution skill Development” (SG-ACCORD), to develop and assess soft skills that are pivotal in educational working contexts (i.e., negotiation, effective communication, intercultural conflict management). The SG-ACCORD has been developed by applying a tailored methodology, namely the Educational Technology-enhanced Role-Playing, addressing two main facets: psycho-pedagogical (theoretical frameworks) and technological (production of artificial worlds based on computer-simulated models). The game is a single-player virtual role-play offering a series of scenarios reflecting the real-life experiences of teachers in which the role of interactions and human factors is crucial. It focuses on the simulation of a dialogue between two characters (an avatar controlled by a human player and a BOT computer-controlled counterpart), enacting interethnic conflicts between teacher and students within realistic school context scenarios. The SG-ACCORD represents a free, easily manageable, and flexible educational tool that can be used as a stand-alone resource and envisages an automatic feedback and debriefing system.

Quantitative risk assessment in El-Jadida (Northern Atlantic Coast of Morocco) for a tsunami scenario equivalent to that of the 1755 Lisbon earthquake

The Atlantic coasts of Morocco are exposed to tsunami risk. Although this risk level is low because of the rarity of tsunamis in the region, a future event would be catastrophic for the Moroccan society and economy because of the numerous issues at stake. In this paper, bathymetric/topographic data and parameters of three known tsunamigenic faults (Marquês do Pombal Fault, Gorringe Bank Fault and Horseshoe Fault) were used to simulate a potential tsunami event in the city of El-Jadida (Morocco) using MIRONE software. The simulation results of the worst-case scenario were then exploited to perform a quantitative risk assessment, using demographic and economic input data. Results show that choosing the Horseshoe Fault as source of the simulated event produces the largest tsunamis; with maximum wave heights ranging from 10 to 27 m. These results are found to be consistent with historical records and computer model simulations from previous studies. Quantitative risk assessment results indicate that the city of El-Jadida is exposed to a high risk of loss of lifes and loss of property with values of the order of 34 lives/year and 14 M$/year, respectively. For this reason, we underline the dire need for the implementation of tsunami risk prevention and mitigation strategies that should prioritize the protection of high-risk areas of the city and its population from a possible future catastrophic event.

Identification of potential inhibitors for Hematopoietic Prostaglandin D2 synthase: Computational modeling and molecular dynamics simulations

To design a new therapeutic agent for Hematopoietic Prostaglandin D2 synthase (hPGDS), a set of 60 molecules with different molecular scaffolds were (range of pIC50 values are from 8.301 to 3.932) considered to create a pharmacophore model. Further, identification of potential hPGDS inhibitors were carried out by using virtual screening with different databases (from 15,74,182 molecules). The molecular screening was performed by using different sequential methods right from Pharmacophore based virtual screening, molecular docking, MM-GBSA studies and ADME property analysis. Based on the molecular screening and visual data analysis, 4 molecules were further subjected to molecular dynamics (MD) simulation study. Outcomes of the present study conclude with a new proposed molecule. Molecule SP1 show a good range of interaction with human hPGDS enzyme in comparison to the marketed compounds i.e., HQL-79, TFC-007, HPGDS inhibitor I and TAS-204.

A fast computational model for the electrophysiology of the whole human heart

In this study we present a novel computational model for unprecedented simulations of the whole cardiac electrophysiology. According to the heterogeneous electrophysiologic properties of the heart, the whole cardiac geometry is decomposed into a set of coupled conductive media having different topology and electrical conductivities: (i) a network of slender bundles comprising a fast conduction atrial network, the AV–node and the ventricular bundles; (ii) the Purkinje network; and (iii) the atrial and ventricular myocardium. The propagation of the action potential in these conductive media is governed by the bidomain/monodomain equations, which are discretized in space using an in–house finite volume method and coupled to three different cell models, the Courtemanche model [1] for the atrial myocytes, the Stewart model [2] for the Purkinje Network and the ten Tusscher–Panfilov model [3] for the ventricular myocytes. The developed numerical model correctly reproduces the cardiac electrophysiology of the whole human heart in healthy and pathologic conditions and it can be tailored to study and optimize resynchronization therapies or invasive surgical procedures. Importantly, the whole solver is GPU–accelerated using CUDA Fortran providing an unprecedented speedup, thus opening the way for systematic parametric studies and uncertainty quantification analyses.

Adaptive Synthesis of Functional Amphiphilic Dendrons as a Novel Approach to Artificial Supramolecular Objects.

Supramolecular structures, such as micelles, liposomes, polymerosomes or dendrimerosomes, are widely studied and used as drug delivery systems. The behavior of amphiphilic building blocks strongly depends on their spatial distribution and shape of polar and nonpolar component. This report is focused on the development of new versatile synthetic protocols for amphiphilic carbosilane dendrons (amp-CS-DDNs) capable of self-assembly to regular micelles and other supramolecular objects. The presented strategy enables the fine modification of amphiphilic structure in several ways and also enables the facile connection of a desired functionality. DLS experiments demonstrated correlations between structural parameters of amp-CS-DDNs and the size of formed nanoparticles. For detailed information about the organization and spatial distribution of amp-CS-DDNs assemblies, computer simulation models were studied by using molecular dynamics in explicit water.

CORR Insights®: Small Random Angular Variations in Pelvic Tilt and Lower Extremity Can Cause Error In Static Image-based Preoperative Hip Arthroplasty Planning: A Computer Modeling Study.

CORR Insights®: Small Random Angular Variations in Pelvic Tilt and Lower Extremity Can Cause Error In Static Image-based Preoperative Hip Arthroplasty Planning: A Computer Modeling Study.

Desynchronization Strain Patterns and Contractility in Left Bundle Branch Block through Computer Model Simulation.

Left bundle branch block (LBBB) is associated with specific septal-to-lateral wall activation patterns which are strongly influenced by the intrinsic left ventricular (LV) contractility and myocardial scar localization. The objective of this study was to propose a computational-model-based interpretation of the different patterns of LV contraction observed in the case of LBBB and preserved contractility or myocardial scarring. Two-dimensional transthoracic echocardiography was used to obtain LV volumes and deformation patterns in three patients with LBBB: (1) a patient with non-ischemic dilated cardiomyopathy, (2) a patient with antero-septal myocardial scar, and (3) a patient with lateral myocardial scar. Scar was confirmed by the distribution of late gadolinium enhancement with cardiac magnetic resonance imaging (cMRI). Model parameters were evaluated manually to reproduce patient-derived data such as strain curves obtained from echocardiographic apical views. The model was able to reproduce the specific strain patterns observed in patients. A typical septal flash with pre-ejection shortening, rebound stretch, and delayed lateral wall activation was observed in the case of non-ischemic cardiomyopathy. In the case of lateral scar, the contractility of the lateral wall was significantly impaired and septal flash was absent. In the case of septal scar, septal flash and rebound stretch were also present as previously described in the literature. Interestingly, the model was also able to simulate the specific contractile properties of the myocardium, providing an excellent localization of LV scar in ischemic patients. The model was able to simulate the electromechanical delay and specific contractility patterns observed in patients with LBBB of ischemic and non-ischemic etiology. With further improvement and validation, this technique might be a useful tool for the diagnosis and treatment planning of heart failure patients needing CRT.

Differences in the mechanics of takeoff in reverse and forward springboard somersaulting dives

ABSTRACT Forward and reverse springboard somersaulting dives use similar approaches with a hurdle step prior to the final board contact phase during which forward rotation is produced in forward takeoffs and backward rotation in reverse takeoffs. This study compared forward and reverse takeoffs for joint strength, activation complexity, technique kinematics, and rotation potential. A planar 8-segment torque-driven computer simulation model of springboard diving takeoff was used to determine isometric joint strength by matching performances of a forward 2½ somersault dive and a reverse 1½ somersault dive. Activation complexity for the reverse takeoff was increased to achieve a similar closeness of match as for the forward takeoff. Takeoff technique was optimised to maximise rotation potential of forward and reverse somersaulting dives. Kinematics at touchdown, lowest point and takeoff were compared for the optimised forward and reverse takeoff simulations. It was found that the optimised reverse somersaulting dive exhibited greater isometric strength for ankle plantarflexion and shoulder flexion, greater joint torque activation complexity for ankle plantarflexion and for knee flexion. There was also less forward motion during board depression, more hip extension and knee flexion during the later stages of board recoil, less capacity for rotation potential, and greater vertical velocity at takeoff.

No Cell Left behind: Automated, Stochastic, Physics-Based Tracking of Every Cell in a Dense, Growing Colony

Motivation: Precise tracking of individual cells—especially tracking the family lineage, for example in a developing embryo—has widespread applications in biology and medicine. Due to significant noise in microscope images, existing methods have difficulty precisely tracking cell activities. These difficulties often require human intervention to resolve. Humans are helpful because our brain naturally and automatically builds a simulation “model” of any scene that we observe. Because we understand simple truths about the world—for example cells can move and divide, but they cannot instantaneously move vast distances—this model “in our heads” helps us to severely constrain the possible interpretations of what we see, allowing us to easily distinguish signal from noise, and track the motion of cells even in the presence of extreme levels of noise that would completely confound existing automated methods. Results: Here, we mimic the ability of the human brain by building an explicit computer simulation model of the scene. Our simulated cells are programmed to allow movement and cell division consistent with reality. At each video frame, we stochastically generate millions of nearby “Universes” and evolve them stochastically to the next frame. We then find and fit the best universes to reality by minimizing the residual between the real image frame and a synthetic image of the simulation. The rule-based simulation puts extremely stringent constraints on possible interpretations of the data, allowing our system to perform far better than existing methods even in the presense of extreme levels of image noise. We demonstrate the viability of this method by accurately tracking every cell in a colony that grows from 4 to over 300 individuals, doing about as well as a human can in the difficult task of tracking cell lineages.

A Review of Computational Simulation Methods for a Ship Advancing in Broken Ice

Apart from breaking level ice, polar ships can interact with broken ice in various scenarios. In recent years, computational simulation models have increasingly been used for the evaluation of ship operability under broken ice conditions, presenting some challenging issues. This paper reviews existing simulation methods used to estimate ship performance and ice loads for ships advancing continuously in broken ice fields. Models for different types of broken ice, including ice floes, ice ridges, brash ice, and sliding ice pieces, are reviewed separately. A ship’s response in broken ice is divided into two categories: resistance, which relates to the overall ship performance, and local loads, which relates to structural safety. This review shows that most existing models are proposed for unbreakable ice particles, which are only applicable to broken ice of small size; most models treat fluid flow with extensive simplification, which does not reflect the influence of a ship’s wake or bow waves, and most models are aimed at resistance estimation, adopting elastic or viscoelastic contact models which do not include ice crushing. As for future work, it is suggested that more effort should be assigned to simulating a ship’s interaction with ice ridges and sliding ice pieces, the modelling of breakable ice floes, and the coupling of the Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD). More attention to the local ice load estimation is also encouraged.

Mechanistic insights into inter-chain disulfide bond reduction of IgG1 and IgG4 antibodies.

Therapeutic monoclonal antibodies (mAbs), primarily immunoglobin G1 (IgG1) and IgG4 with an engineered CPPC motif in its hinge region, are predominant biologics. Inter-chain disulfide bonds of IgG mAbs are crucial to maintaining IgG integrity. Inter-chain disulfide bond-reduced low molecular weight (LMW) is considered as one of quality attributes of IgG drug substance and is observed in drug substance manufacturing. In this study, we demonstrate that IgG1 and IgG4 are susceptible to the reducing agent TCEP differently and they follow different pathways to form LMWs. Our study shows that IgG1 is more sensitive to TCEP than IgG4. Both therapeutic IgG1 and human blood plasma IgG1 follow a heavy-heavy-light chain (HHL) pathway, featured with HHL and HH as intermediate species. Human blood plasma IgG4 with a CPSC motif in its hinge region follows heavy-light chain (HL) pathway, featured with HL as the intermediate species. However, therapeutic IgG4 follows a hybrid pathway with the HL pathway as the primary and the HHL pathway as the secondary. These experimental observations are further explained using solvent accessibility of inter-chain disulfide bonds obtained from computational modeling and molecular dynamics simulations. Findings from this study provide mechanistic insights of LMW formation of IgG1 and IgG4, which suggest selection of IgG1 or IgG4 for bispecific antibodies and cysteine-based antibody-drug conjugates. KEY POINTS: • Experimentally discovered preferable disulfide bond reduction pathways between IgG1 and IgG4 antibodies, driven by the different solvent accessibilities of these disulfide bonds. • Computationally explained the solvent accessibility aided by molecular dynamics simulations. • Provided insights in developing robust biologics process and designing bispecific antibodies and cysteine-based antibody-drug conjugates.

A 3D-Printed Continuously Variable Transmission for an Electric Vehicle Prototype

This paper aims to present the design of a new 3D-printed continuously variable transmission (CVT) developed for an electric vehicle prototype competing in Shell Eco-marathon electric battery category, a world-wide energy efficiency competition sponsored by Shell. The proposed system is composed of a polymeric conic geared friction wheel assembled in the motor axle and directly coupled to the rear tire of the vehicle. The conical shape allows to implement a continuous variation of the geared friction wheel diameter in contact with the tire. The motor with the geared friction wheel was mounted over a board with linear bearings, allowing the speed ratio to change by moving the board laterally. A computational simulation model of a prototype electric vehicle with the proposed 3D-printed CVT was created in Matlab/Simulink environment to obtain the traction force in the geared friction wheel and also to analyze the vehicle performance. The simulation results demonstrated possibilities of increasing vehicle speed range output and available torque in the rear traction wheel. Also, it is shown with the simulated model that the designed CVT consumes 10.46% less energy than a fixed transmission ratio, demonstrating the CVT concept’s potential for battery consumption reduction. Lastly, a 3D-printing slicing software with an optimization algorithm plug-in was used to determine the best printing parameters for the conic geared friction wheel based on the tangential force, maximum displacement and safety factor. When compared to the original part with a 100% infill density, the optimized solution reduced the component mass by about 12% while maintaining safe mechanical resistance and stiffness.