Real-time Computer Model Research Articles

Enhanced Multimodal Nonparametric Probabilistic Method for Model-Form Uncertainty Quantification and Digital Twinning

The nonparametric probabilistic method (NPM) is a physics-based machine learning approach for model-form (MF) uncertainty quantification (UQ), model updating, and digital twinning. It extracts from reference data information not captured by a real-time computational model and infuses it into a “hyperparameterized,” stochastic version of this model by solving an inverse statistical problem formulated using a loss function and a few hyperparameters. The loss function is designed such that the mean value and statistical fluctuations of some quantities of interest predicted using the real-time stochastic model match target values obtained from the reference data. NPM’s performance hinges upon the efficient minimization of the loss function, which is unfortunately stochastic and nonconvex and thus prone to getting the optimization procedure trapped in suboptimal local minima. The latter scenario is exacerbated when the reference data is scarce. The paper addresses these issues by adopting the squared quadratic Wasserstein distance as the measure of dissimilarity between two different sets of data and by reformulating NPM’s inverse statistical problem as a multimodal data-assimilation problem. The potential of the resulting enhanced NPM for MF-UQ, model updating, and digital twinning is demonstrated using numerical simulations relevant to applications in structural dynamics, including structural health monitoring.

A model-Based Mechatronic System Design and Integration Process

In contemporary mechatronic product development, embracing an interdisciplinary approach has become imperative to manage potential integration risks. This research paper introduces a viable solution that combines Automation Studio and the VDI 2206 methodology to design mechatronic systems. The study's findings highlight the efficacy of this interdisciplinary approach in effectively addressing early challenges associated with multi-domain integration. It enables simultaneous evaluation and resolution of limitations inherent in traditional design methods. Successfully applied to develop an automated garment folding machine with a PLC controller, the proposed process proves to be a valuable tool in optimizing mechatronic system development. The system, designed using this process, relies on a real-time computational model as its foundation, laying the groundwork for constructing a digital twin in the future. This ensures a comprehensive representation of the system, facilitating enhanced understanding and performance assessment during the development and operational phases. The adoption of such an approach signifies a significant step forward in advancing mechatronic engineering and ensuring the successful realization of complex and efficient systems.

A digital twin concept for optimizing the use of high-temperature heat pumps to reduce waste in industrial renewable energy systems

In light of the global industrial sector's steadfast pursuit of sustainable solutions to mitigate carbon emissions and efficiently minimize energy inefficiencies, the significance of novel approaches to energy optimization becomes increasingly evident. This research presents a novel digital twin concept that is designed to enhance the efficiency and effectiveness of high-temperature heat pumps in industrial renewable energy systems. Through the utilization of real-time data and complex computer modeling techniques, our proposed digital twin model seamlessly presents a comprehensive perspective on energy flows. This approach identifies inefficiencies and delivers practical insights to mitigate waste. The incorporation of this approach into pre-existing eco-conscious renewable energy systems has the potential to greatly enhance the effectiveness, predictability, and long-term viability of industrial processes. The empirical findings, obtained from multiple case studies conducted in industrial settings, provide evidence of the potential benefits in terms of energy waste reduction, and maximize the durability of systems. The results of our initial studies provide a foundation for the utilization of digital twin technologies in the field of industrial renewable energy systems optimization, representing a significant advancement towards a more environmentally sustainable industrial landscape.

Uniform Droplet Spraying of Magnesium Alloys: Modeling of Apollonian Fractal Structures on Micrograph Sections

A variety of advanced manufacturing processes have been developed based on the concept of rapid solidification processing (RSP), such as uniform droplet spraying (UDS) for the additive manufacturing of metals and alloys. This article introduces a morphological simulation of fractal dendric structures deposited by UDS of magnesium (Mg) alloys on two-dimensional (2D) planar sections. The fractal structure evolution is modeled as Apollonian packs of generalized ellipsoidal domains growing out of nuclei and dendrite arm fragments. The model employs descriptions of the dynamic thermal field based on superposed Green’s/Rosenthal functions with source images for initial/boundary effects, along with alloy phase diagrams and the classical solidification theory for nucleation and fragmentation rates. The initiation of grains is followed by their free and constrained growth by adjacent domains, represented via potential fields of level-set methods, for the effective mapping of the solidified topology and its metrics (grain size and fractal dimension of densely packed domains). The model is validated by comparing modeling results against micrographs of three UDS-deposited Mg–Zn–Y alloys. The further evolution of this real-time computational model and its application as a process observer for feedback control in 3D printing, as well as for off-line material design and optimization, is discussed.

Transformation and Evaluation of the MIMIC Database in the OMOP Common Data Model: Development and Usability Study.

BackgroundIn the era of big data, the intensive care unit (ICU) is likely to benefit from real-time computer analysis and modeling based on close patient monitoring and electronic health record data. The Medical Information Mart for Intensive Care (MIMIC) is the first open access database in the ICU domain. Many studies have shown that common data models (CDMs) improve database searching by allowing code, tools, and experience to be shared. The Observational Medical Outcomes Partnership (OMOP) CDM is spreading all over the world.ObjectiveThe objective was to transform MIMIC into an OMOP database and to evaluate the benefits of this transformation for analysts.MethodsWe transformed MIMIC (version 1.4.21) into OMOP format (version 5.3.3.1) through semantic and structural mapping. The structural mapping aimed at moving the MIMIC data into the right place in OMOP, with some data transformations. The mapping was divided into 3 phases: conception, implementation, and evaluation. The conceptual mapping aimed at aligning the MIMIC local terminologies to OMOP's standard ones. It consisted of 3 phases: integration, alignment, and evaluation. A documented, tested, versioned, exemplified, and open repository was set up to support the transformation and improvement of the MIMIC community's source code. The resulting data set was evaluated over a 48-hour datathon.ResultsWith an investment of 2 people for 500 hours, 64% of the data items of the 26 MIMIC tables were standardized into the OMOP CDM and 78% of the source concepts mapped to reference terminologies. The model proved its ability to support community contributions and was well received during the datathon, with 160 participants and 15,000 requests executed with a maximum duration of 1 minute.ConclusionsThe resulting MIMIC-OMOP data set is the first MIMIC-OMOP data set available free of charge with real disidentified data ready for replicable intensive care research. This approach can be generalized to any medical field.

Hemodynamics-driven mathematical model of first and second heart sound generation.

We propose a novel, two-degree of freedom mathematical model of mechanical vibrations of the heart that generates heart sounds in CircAdapt, a complete real-time model of the cardiovascular system. Heart sounds during rest, exercise, biventricular (BiVHF), left ventricular (LVHF) and right ventricular heart failure (RVHF) were simulated to examine model functionality in various conditions. Simulated and experimental heart sound components showed both qualitative and quantitative agreements in terms of heart sound morphology, frequency, and timing. Rate of left ventricular pressure (LV dp/dtmax) and first heart sound (S1) amplitude were proportional with exercise level. The relation of the second heart sound (S2) amplitude with exercise level was less significant. BiVHF resulted in amplitude reduction of S1. LVHF resulted in reverse splitting of S2 and an amplitude reduction of only the left-sided heart sound components, whereas RVHF resulted in a prolonged splitting of S2 and only a mild amplitude reduction of the right-sided heart sound components. In conclusion, our hemodynamics-driven mathematical model provides fast and realistic simulations of heart sounds under various conditions and may be helpful to find new indicators for diagnosis and prognosis of cardiac diseases.New & noteworthyTo the best of our knowledge, this is the first hemodynamic-based heart sound generation model embedded in a complete real-time computational model of the cardiovascular system. Simulated heart sounds are similar to experimental and clinical measurements, both quantitatively and qualitatively. Our model can be used to investigate the relationships between heart sound acoustic features and hemodynamic factors/anatomical parameters.

Assessment of stress–strain behavior of shaft lining in bottomhole area during sinking by real-time monitoring and computer modeling data

With an increase in the depth of shafting and subsequent risk growth, it becomes necessary to make a maximum accurate estimate of the actual stress–strain behavior of the shaft lining. Real-time monitoring and numerical simulation of the bottomhole zone of a shaft in the process of sinking is proposed as an effective approach to the solution of this problem. The results of an experimental check in three sites of shafts in similar engineering–geological conditions are presented. The real-time monitoring provided control of tensile forces in rock bolts before installation of the main support. Rock bolts 1.8 m long were used with full- and partiallength grouting in the hole. In each test area, 18 strain gauged rock bolts were installed with tensometric sensors glued along the rock bolts. As a result of the research, an array of data on 486 values of tensile forces is obtained. The graphs of the force variation along the rock bolts are plotted at different sizes of its grouting in the borehole. In all experimental sites, the minimum tensional forces in the rock bolts were observed when the bolts were fully grouted in the borehole. When the bolts were partially grouted, the forces were 1.4–1.7 times greater. At the second stage of the research, the 3D finite element models were built for the bottomhole area of vertical shafts in three experimental areas. The calculation took into account the deformation nonlinearity by using stepwise iterative procedures. The comparison of the experimental and numerical simulation results shows the similar qualitative distribution of forces along the rock bolts. According to the quantitative analysis, the maximum deviation of the force values never exceeds 19%. The higher calculated values can be explained by the fact that numerical modeling neglects structural yielding of the rock bolts. The obtained comparative data confirm the correctness of the numerical models. Based on that, the numerical models were then used to find the maximal stresses in the shaft lining, and the structure strength was estimated. As the main method for increasing the bearing capacity of the lining, it is recommended to use concrete of higher strength at depths greater than 700 m.

Thermal Management of Edge-Cooled 1 kW Portable Proton Exchange Membrane Fuel Cell Stack

Air-cooled proton exchange membrane (PEM) fuel cell stacks are gaining momentum as power sources for portable applications such as electric bikes, unmanned aerial vehicles (UAVs), forklifts, etc. Usually the power of portable stacks (PS) is up to several kW [1,2]. Most of the heat generated during PS operation is dissipated into the surrounding atmosphere via forced air convection along the cooling channels or edge-cooling fins, while the higher power stacks require liquid cooling. The emphasis during the design phase of PS is primarily directed towards determining the most suitable material for bipolar plates and the accompanying thermal management. Some of the thermal management objectives are: (i) ensuring the appropriate heat transfer from the stack during startup, i.e. accurately determining the required convection flow rate, to achieve sufficiently high operating temperature from startup at ambient temperature, thus preventing flooding (occurring if the flow rate is high and temperature of the stack is low) or membrane dehydration (occurring if the flow rate is low and temperature inside the stack is high); (ii) ensuring sufficiently high heat removal rates via forced air convection during the operation characterized by stable temperature of the stack, i.e. loosely termed steady-state operation; (iii) ensuring as low as possible temperature difference between the inside and outside portions of the stack by choosing the materials with favorable thermal properties; (iv) properly design the stack and edge-cooling fins to ensure sufficiently high heat removal rates; (v) design the frame for the stack which will ensure that the cooling air is directed to uniformly flow along the edge-cooling fins. In previous studies [3,4] it was shown that the operating temperature inside PEM fuel cell is highly non-uniform and it is not accurate to represent the operating temperature with just one parameter, while at the same time if the temperature profile is controlled it can be exploited to result in high performance of the cell by manipulating the water vapor saturation profile, i.e. relative humidity profile inside the cell. The main contributions of this work to the research field are evident in outlining that the commonly used lumped models can be misleading for dynamic analysis of PEM fuel cell performance due to inability to accurately calculate the maximal temperature inside the stack and this work also outlines under which circumstances the lumped models can be used. This work also presents a novel transient CFD model for analysis of thermal management of PS which gives insight in mass and heat transfer both inside and outside of the cell (internal heat and mass transfer and forced air convection edge-cooling), while other works focus on only one aspect and simplify the other to a significant extent.In order to study thermal management influence on the performance od 1kW edge-cooled proton exchange membrane fuel cell stack without external humidification comprehensive numerical analyses are conducted. Two numerical approaches are considered and compared for a prescribed load profile: (i) lumped model and novel (ii) real-time transient computational fluid dynamics model incorporating realistic modeling of forced air convection on the edge-cooling of the stack. The developed computational fluid dynamics model is used to study the influence of (i) bipolar plate materials (ii) operating delta pressure along the flow field and (iii) different cooling fin configurations on the water and heat balance inside the stack. The results indicate that (i) maximal and average temperatures of the stack are almost linearly correlated to the thermal conductivity of bipolar plate materials and maximal temperatures can be significantly higher (ii) the operating delta pressure can be manipulated to increase the performance of the stack and (iii) the cooling fin redesign has major influence on the overall temperature uniformity across the stack. Additionally, the heat transfer between the stack and metal hydride tank is studied.

Multivariable control of ball-milled reactive material composition and structure

In reactive bimetallic compounds such as Ni–Al multilayers, desirable thermo-kinetic properties upon ignition require simultaneously controlled geometric microstructure and material composition. This article establishes fundamental dynamical models of plastic deformation and material diffusion in ball milling processing of particulates from Ni and Al powders, for the purpose of designing and implementing feedback control strategies for process control. The role of heat dissipation from plastic yield and friction slip in affecting compressibility and diffusivity of the material is elucidated. The different sensitivity of compressibility and diffusivity to thermal power is exploited by introducing multivariable control of both bilayer thickness and penetration depth simultaneously, using a real-time computational model as an observer with adaptation informed by infrared measurements of external vial temperature. The proposed control scheme is tested on a laboratory low-energy ball milling system and demonstrated to effectively modulate power intensity and process duration to obtain the desired microstructure and material composition.

Thermal management of edge-cooled 1 kW portable proton exchange membrane fuel cell stack

Comprehensive numerical analyses are conducted to study the influence of thermal management on performance of 1 kW edge-cooled proton exchange membrane fuel cell stack without external humidification. The experimental stack and numerical three-dimensional computational fluid dynamics model are characterized by several novelty aspects. Two numerical approaches are considered and compared for a prescribed load profile: (i) lumped model and novel (ii) real-time transient computational fluid dynamics model incorporating realistic modeling of forced air convection on the edge-cooling of the stack. The novelty of the developed computational fluid dynamics model is the capability to give insight in the transient results in only a fraction of time vs. experimental testing (40 min vs. 4 h) and other computational fluid dynamics models of fuel cells which are only capable of steady-state analysis. The developed computational fluid dynamics model is used to study the influence of (i) bipolar plate materials (ii) operating delta pressure along the flow field and (iii) different cooling fin configurations on the water and heat balance inside the stack. The results indicate that (i) maximal and average temperatures of the stack are almost linearly correlated to the thermal conductivity of bipolar plate materials and maximal temperatures can be significantly higher (ii) the operating delta pressure can be manipulated to increase the performance of the stack and (iii) the cooling fin redesign has major influence on the overall temperature uniformity across the stack. Additionally, the heat transfer between the stack and metal hydride tank is studied.

Optimal Tuner Selection using Kalman Filter for a Real-Time Modular Gas Turbine Model

In this study, a real-time flexible modular modeling approach for the simulation of gas turbine engines dynamic behavior based on nonlinear thermodynamic and dynamic laws is addressed. The introduced model, which is developed in Matlab-Simulink environment, is an object-oriented high speed real-time computer model and is capable of simulating the dynamic behavior of a broad group of gas turbine engines due to its modular structure. Moreover, a Kalman filter-based model tuning procedure is applied to decrease the modeling errors. Modeling errors are defined as the mismatch between simulation results and available experimental data. This tuning procedure is an underdetermined estimation problem, where there are more tuning parameters than available measured data. Here, an innovative approach to produce a tuning parameter vector is introduced. This approach is based on seeking an optimal initial value for the Kalman filter tuning procedure. Three simulation studies are carried out in this paper to demonstrate the advantages, capabilities and performance of the proposed scheme. Furthermore, simulation results are compared with manufacturer’s published data, and with the experimental results gathered in either turbo-generator or turbo-compressor applications. Computational time requirement of the model is discussed at the end of the paper.

Control of inductors for formation of the required temperature profile in tasks of control and design

Here, we introduce current design trends in modern machine building inductor installations on the example of inductor installations for heating before treatment. A particular focus is given to the numerical simulation, whose importance increases due to modern strict requirements for the technological process as well as computational power increase. Nowadays, numerical computations are required not only to calculate electromagnetic and thermal fields for separate devices but also to simulate the whole technology. New trends in computing developments allow using real-time computational model control by inverse solution (inductor parameters calculation according to the given temperature profile).

Basic Concepts in Environmental Computer Control of Agricultural Systems

The article outlines how computer control technology is used in agriculture to monitor and manage environmental conditions for optimal production. It discusses the complexity of agricultural systems, the hardware and software components involved in control systems, and various control strategies. It also mentions commercially available systems, do-it-yourself options, and emerging technologies like real-time expert systems, computer modeling, and robotics. Overall, it suggests that computer-controlled systems are becoming increasingly important in agriculture, offering improved efficiency and resource management.

Left Ventricular Unloading During Veno-Arterial ECMO: A Simulation Study.

Veno-arterial extracorporeal membrane oxygenation (VA ECMO) is widely used in cardiogenic shock. It provides systemic perfusion, but left ventricular (LV) unloading is suboptimal. Using a closed-loop, real-time computer model of the human cardiovascular system, cardiogenic shock supported by peripheral VA ECMO was simulated, and effects of various adjunct LV unloading interventions were quantified. After VA ECMO initiation (4 L/min) in cardiogenic shock (baseline), hemodynamics improved (increased to 85 mm Hg), while LV overload occurred (10% increase in end-diastolic volume [EDV], and 5 mm Hg increase in pulmonary capillary wedge pressure [PCWP]). Decreasing afterload (65 mm Hg mean arterial pressure) and circulating volume (-800 mL) reduced LV overload (12% decrease in EDV and 37% decrease in PCWP) compared with baseline. Additional intra-aortic balloon pumping only marginally decreased cardiac loading. Instead, adjunct Impella™ enhanced LV unloading (23% decrease in EDV and 41% decrease in PCWP). Alternative interventions, for example, left atrial/ventricular venting, yielded substantial unloading. We conclude that real-time simulations may provide quantitative clinical measures of LV overload, depending on the degree of VA ECMO support and adjunct management. Simulations offer insights into individualized LV unloading interventions in cardiogenic shock supported by VA ECMO as a proof of concept for potential future applications in clinical decision support, which may help to improve individualized patient management in complex cardiovascular disease.

A model for real-time computation of fuselage-rotor interference

A simple analytical real-time capable model to account for fuselage-induced velocities at rotor blade elements is described at the example of the Bo105 fuselage. Data of the fuselage-induced flow fields in the volume of rotor operation above the fuselage are first computed by a panel method in the range of angle of attack and sideslip of [Formula: see text]. The model parameters are then estimated based on these data. The usefulness of the model in combinations of angle of attack and sideslip is demonstrated.

A real-time computational model for estimating kinematics of ankle ligaments

Background: An accurate assessment of ankle ligament kinematics is crucial in understanding the injury mechanisms and can help to improve the treatment of an injured ankle, especially when used in conjunction with robot-assisted therapy. A number of computational models have been developed and validated for assessing the kinematics of ankle ligaments. However, few of them can do real-time assessment to allow for an input into robotic rehabilitation programs. Method: An ankle computational model was proposed and validated to quantify the kinematics of ankle ligaments as the foot moves in real-time. This model consists of three bone segments with three rotational degrees of freedom (DOFs) and 12 ankle ligaments. This model uses inputs for three position variables that can be measured from sensors in many ankle robotic devices that detect postures within the foot–ankle environment and outputs the kinematics of ankle ligaments. Validation of this model in terms of ligament length and strain was conducted by comparing it with published data on cadaver anatomy and magnetic resonance imaging. Results: The model based on ligament lengths and strains is in concurrence with those from the published studies but is sensitive to ligament attachment positions. Conclusions: This ankle computational model has the potential to be used in robot-assisted therapy for real-time assessment of ligament kinematics. The results provide information regarding the quantification of kinematics associated with ankle ligaments related to the disability level and can be used for optimizing the robotic training trajectory.

Computational and Optimization Design in Geometric Acoustics

The use of 3D computer modeling tools through the 90s has revolutionized the practice of architecture. Coupled with new fabrication processes, these have introduced new territories for architectural design. Such techniques are also available to acoustic designers for the shaping of spaces. With 3D modeling programs such as Rhino3D and Grasshopper incorporating NURBS, geometries can be easily adjusted to meet both aesthetic and functional objectives. Control points of NURBS elements give access to the parameterization of geometries which subsequently can be assigned variables and open the way to computational design optimization. Through several performing arts project examples, this paper gives an overview of processes used today by acousticians to refine designs either through iterative design, auralization, optimization algorithms and real-time computer modeling. Contextualized with design practices from different periods of history, the paper discusses the relevance of computational and optimization tools in the design process of shaping rooms, walls and reflectors and how these methods can support creativity, accelerate solution finding, and interface with complex architectural ideas.

Dynamic Action Potential Clamp Investigation of Pro-Arrhythmic Risk of Drugs Binding to hERG Potassium Channels

Many commonly used drugs can bind to and block the hERG channel and cause the potentially life threatening acquired long-QT syndrome.Whilst obtaining an IC50 for drug block of hERG is relatively straight forward, this is a poor surrogate for risk of pro-arrhythmia. Predicting the overall consequences of hERG drug block on cardiac electrical activity is complicated by the fact that the effect of hERG channel block varies in different cells (e.g. epicardial, mid-myocardial, endocardial, Purkinje) of the heart. Furthermore it is significantly altered by the electrical remodeling that occurs in many chronic heart conditions. With the aging of our population and an increasing proportion of people with chronic heart conditions it is especially important to understand how disease states affect the consequences of hERG drug block and risk of pro-arrhythmia.Here we describe a recently developed dynamic action potential clamp system (dAPC) to investigate the effect of hERG block on cardiomyocytes. The system consists of conventional whole cell voltage clamp study of ion channels in mammalian expression systems, coupled to a real time computer model of human cardiomyocyte action. The dAPC system integrates the current recordings from a patch clamped cell into an in-silico cell model, the output of which is then used to determine the voltage of the patch clamped cell. When used in combination with a state of the art drug perfusion system this integrative approach will permit testing of drugs on specified ion channels in a physiologically relevant environment, something that is not possible with conventional patch clamp methods.

The Stomatogastric Nervous System as a Model for Studying Sensorimotor Interactions in Real-Time Closed-Loop Conditions

The perception of proprioceptive signals that report the internal state of the body is one of the essential tasks of the nervous system and helps to continuously adapt body movements to changing circumstances. Despite the impact of proprioceptive feedback on motor activity it has rarely been studied in conditions in which motor output and sensory activity interact as they do in behaving animals, i.e., in closed-loop conditions. The interaction of motor and sensory activities, however, can create emergent properties that may govern the functional characteristics of the system. We here demonstrate a method to use a well-characterized model system for central pattern generation, the stomatogastric nervous system, for studying these properties in vitro. We created a real-time computer model of a single-cell muscle tendon organ in the gastric mill of the crab foregut that uses intracellular current injections to control the activity of the biological proprioceptor. The resulting motor output of a gastric mill motor neuron is then recorded intracellularly and fed into a simple muscle model consisting of a series of low-pass filters. The muscle output is used to activate a one-dimensional Hodgkin–Huxley type model of the muscle tendon organ in real-time, allowing closed-loop conditions. Model properties were either hand tuned to achieve the best match with data from semi-intact muscle preparations, or an exhaustive search was performed to determine the best set of parameters. We report the real-time capabilities of our models, its performance and its interaction with the biological motor system.

An Introduction to Time-Constrained Automata

We present time-constrained automata (TCA), a model for hard real-time computation in which agents behaviors are modeled by automata and constrained by time intervals. TCA actions can have multiple start time and deadlines, can be aperiodic, and are selected dynamically following a graph, the time-constrained automaton. This allows expressing much more precise time constraints than classical periodic or sporadic model, while preserving the ease of scheduling and analysis. We provide some properties of this model as well as their scheduling semantics. We show that TCA can be automatically derived from source-code, and optimally scheduled on single processors using a variant of EDF. We explain how time constraints can be used to guarantee communication determinism by construction, and to study when possible agent interactions happen.