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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

2007 Lunar Regolith Simulant Workshop Overview

The National Aeronautics and Space Administration (NASA) vision has as a cornerstone, the establishment of an Outpost on the Moon. This Lunar Outpost will eventually provide the necessary planning, technology development, and training for a manned mission to Mars in the future. As part of the overall activity, NASA is conducting Earth-based research and advancing technologies to a Technology Readiness Level (TRL) 6 maturity under the Exploration Technology Development Program that will be incorporated into the Constellation Project as well as other projects. All aspects of the Lunar environment, including the Lunar regolith and its properties, are important in understanding the long-term impacts to hardware, scientific instruments, and humans prior to returning to the Moon and living on the Moon. With the goal of reducing risk to humans and hardware and increasing mission success on the Lunar surface, it is vital that terrestrial investigations including both development and verification testing have access to Lunar-like environments. The Marshall Space Flight Center (MSFC) is supporting this endeavor by developing, characterizing, and producing Lunar simulants in addition to analyzing existing simulants for appropriate applications. A Lunar Regolith Simulant Workshop was conducted by MSFC in Huntsville, Alabama, in October 2007. The purpose of the Workshop was to bring together simulant developers, simulant users, and program and project managers from ETDP and Constellation with the goals of understanding users' simulant needs and their applications. A status of current simulant developments such as the JSC-1A (Mare Type Simulant) and the NASA/U.S. Geological Survey Lunar Highlands-Type Pilot Simulant (NU-LHT-1 M) was provided. The method for evaluating simulants, performed via Figures of Merit (FoMs) algorithms, was presented and a demonstration was provided. The four FoM properties currently being assessed are: size, shape, density, and composition. Some of the Workshop findings include: simulant developers must understand simulant users' needs and applications; higher fidelity simulants are needed and needed in larger quantities now; simulants must be characterized to allow "apples-to-apples" comparison of test results; simulant users should confer with simulant experts to assist them in the selection of simulants; safety precautions should be taken in the handling and use of simulants; shipping, storing, and preparation of simulants have important implications; and most importantly, close communications among the simulant community must be maintained and will be continued via telecoms, meetings, and an annual Lunar Regolith Simulant Workshop.

McLemore, Carole A.↗
NASA NTRS2007

2007 Lunar Regolith Simulant Workshop Overview

The National Aeronautics and Space Administration (NASA) vision has as a cornerstone, the establishment of an Outpost on the Moon. This Lunar Outpost will eventually provide the necessary planning, technology development, and training for a manned mission to Mars in the future. As part of the overall activity, NASA is conducting Earth-based research and advancing technologies to a Technology Readiness Level (TRL) 6 maturity under the Exploration Technology Development Program that will be incorporated into the Constellation Project as well as other projects. All aspects of the Lunar environment, including the Lunar regolith and its properties, are important in understanding the long-term impacts to hardware, scientific instruments, and humans prior to returning to the Moon and living on the Moon. With the goal of reducing risk to humans and hardware and increasing mission success on the Lunar surface, it is vital that terrestrial investigations including both development and verification testing have access to Lunar-like environments. The Marshall Space Flight Center (MSFC) is supporting this endeavor by developing, characterizing, and producing Lunar simulants in addition to analyzing existing simulants for appropriate applications. A Lunar Regolith Simulant Workshop was conducted by MSFC in Huntsville, Alabama, in October 2007. The purpose of the Workshop was to bring together simulant developers, simulant users, and program and project managers from ETDP and Constellation with the goals of understanding users' simulant needs and their applications. A status of current simulant developments such as the JSC-1A (Mare Type Simulant) and the NASA/U.S. Geological Survey Lunar Highlands-Type Pilot Simulant (NU-LHT-1M) was provided. The method for evaluating simulants, performed via Figures of Merit (FoMs) algorithms, was presented and a demonstration was provided. The four FoM properties currently being assessed are: size, shape, density, and composition. Some of the Workshop findings include: simulant developers must understand simulant users' needs and applications; higher fidelity simulants are needed and needed in larger quantities now; simulants must be characterized to allow "apples-to-apples" comparison of test results; simulant users should confer with simulant experts to assist them in the selection of simulants; safety precautions should be taken in the handling and use of simulants; shipping, storing, and preparation of simulants have important implications; and most importantly, close communications among the simulant community must be maintained and will be continued via telecoms, meetings, and an annual Lunar Regolith Simulant Workshop.

McLemore, Carole A.↗
NASA NTRS2008

Simulation Results for Airborne Precision Spacing along Continuous Descent Arrivals

This paper describes the results of a fast-time simulation experiment and a high-fidelity simulator validation with merging streams of aircraft flying Continuous Descent Arrivals through generic airspace to a runway at Dallas-Ft Worth. Aircraft made small speed adjustments based on an airborne-based spacing algorithm, so as to arrive at the threshold exactly at the assigned time interval behind their Traffic-To-Follow. The 40 aircraft were initialized at different altitudes and speeds on one of four different routes, and then merged at different points and altitudes while flying Continuous Descent Arrivals. This merging and spacing using flight deck equipment and procedures to augment or implement Air Traffic Management directives is called Flight Deck-based Merging and Spacing, an important subset of a larger Airborne Precision Spacing functionality. This research indicates that Flight Deck-based Merging and Spacing initiated while at cruise altitude and well prior to the Terminal Radar Approach Control entry can significantly contribute to the delivery of aircraft at a specified interval to the runway threshold with a high degree of accuracy and at a reduced pilot workload. Furthermore, previously documented work has shown that using a Continuous Descent Arrival instead of a traditional step-down descent can save fuel, reduce noise, and reduce emissions. Research into Flight Deck-based Merging and Spacing is a cooperative effort between government and industry partners.

Barmore, Bryan E.↗
DOE OSTI2024

Adaptive Computing and Multi-Fidelity Strategies for Control, Design and Scale-Up of Renewable Energy Applications

We describe our ongoing research in adaptive computing and multi-fidelity modeling strategies. Our goal is to use a combination of low- and high-fidelity simulation models to enable computationally efficient optimization and uncertainty quantification. We develop optimization formulations that take into account the compute resources currently available, which act as a constraint with regards to the fidelity level simulation we can run while maximizing information gain. These strategies are being implemented into a software framework with a generalized API allowing its application to a broad range of applications, from power grid stability and buildings control to material synthesis and biofuels processing. We will discuss a few examples from these applications that can benefit from this approach, especially when considering challenges arising in scaling up experiments and simulations.

adaptive computing↗
DOE OSTI2017

Orthogonal Gaussian process models

Gaussian processes models are widely adopted for nonparameteric/semi-parametric modeling. Identifiability issues occur when the mean model contains polynomials with unknown coefficients. Though resulting prediction is unaffected, this leads to poor estimation of the coefficients in the mean model, and thus the estimated mean model loses interpretability. This paper introduces a new Gaussian process model whose stochastic part is orthogonal to the mean part to address this issue. As a result, this paper also discusses applications to multi-fidelity simulations using data examples.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Modeling and Simulation of Phased Array Antennas to Support Next-Generation Satellite Design

Developing enhanced simulation capabilities has become a significant priority for the Space Communications and Navigation (SCaN) project at NASA as new space communications technologies are proposed to replace aging NASA communications assets, such as the Tracking and Data Relay Satellite System (TDRSS). When developing the architecture for these new space communications assets, it is important to develop updated modeling and simulation methodologies, such that competing architectures can be weighed against one another and the optimal path forward can be determined. There have been many simulation tools developed here at NASA for the simulation of single RF link budgets, or for the modeling and simulation of an entire network of spacecraft and their supporting SCaN network elements. However, the modeling capabilities are never fully complete and as new technologies are proposed, gaps are identified. One such gap is the ability to rapidly develop high fidelity simulation models of electronically steerable phased array systems. As future relay satellite architectures are proposed that include optical communications links, electronically steerable antennas will become more desirable due to the reduction in platform vibration introduced by mechanically steerable devices. In this research, we investigate how modeling of these antennas can be introduced into out overall simulation and modeling structure. The ultimate goal of this research is two-fold. First, to enable NASA engineers to model various proposed simulation architectures and determine which proposed architecture meets the given architectural requirements. Second, given a set of communications link requirements for a proposed satellite architecture, determine the optimal configuration for a phased array antenna. There is a variety of tools available that can be used to model phased array antennas. To meet our stated goals, the first objective of this research is to compare the subset of tools available to us, trading-off modeling fidelity of the tool with simulation performance. When comparing several proposed architectures, higher- fidelity modeling may be desirable, however, when iterating a proposed set of communication link requirements across ranges of phased array configuration parameters, the practicality of performance becomes a significant requirement. In either case, a minimum simulation - fidelity must be met, regardless of performance considerations, which will be discussed in this research. Given a suitable set of phased array modeling tools, this research then focuses on integration with current SCaN modeling and simulation tools. While properly modeling the antenna elements of a system are vital, this is only a small part of the end-to-end communication path between a satellite and the supporting ground station and/or relay satellite assets. To properly model a proposed simulation architecture, this toolset must be integrated with other commercial and government development tools, such that the overall architecture can be examined in terms of communications, reliability, and cost. In this research, integration with previously developed communication tools is investigated.

Phased Array↗
DOE OSTI2026

Adaptive Computing and Multi-Fidelity Learning

We describe our ongoing research in adaptive computing. Our goal is to use a combination of low- and high-fidelity simulation models to enable computationally efficient optimization and uncertainty quantification. We develop optimization formulations that take into account the compute resources currently available, which act as a constraint with regards to the fidelity level simulation we can run while maximizing information gain. We will discuss a few application examples that can benefit from this approach, especially when considering challenges arising in scaling up experiments and simulations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

A Comparison of Rotor Disk Modeling and Blade-Resolved CFD Simulations for NASA's Tiltwing Air Taxi

A multi-fidelity computational fluid dynamics analysis is carried out for NASA’s tiltwing air taxi concept operating in airplane and helicopter mode. High-fidelity simulations are computationally expensive due to individual rotor blade modeling in a time-dependent computational domain with rotating grids. The mid-fidelity rotor disk option, in its source term implementation, is explored as a more affordable alternative. Computations are performed with NASA’s OVERFLOW flow solver loosely-coupled with the comprehensive code CAMRAD II for appropriate rotor trim. Detailed comparisons are shown for the trim solution, airloads, wake geometry, and rotor performance. While the rotor disk model is able to capture the flow field with satisfactory agreement in airplane mode, it faces difficulties in helicopter mode due to the three-dimensional effects of the wake. Although this study is limited to a specific vehicle geometry, it is expected that the results are somewhat generalizable to the analysis of multi-rotor configurations.

ARMD↗
DOE OSTI2024

Comparison of volatiles evolving from selected highland and mare lunar regolith simulants during vacuum sintering

Volatiles evolving from JSC-1A, NU-LHT-4M and CSM-LHT-1G lunar regolith simulants during in vacuo thermal processing were analyzed using mass spectrometry as a function of temperature. Two high-fidelity simulants, JSC-1A (mare) and NU-LHT-4M (highland), were compared to a newly developed CSM-LHT-1G highland simulant, modified to closely match lunar geochemistry. Large autogenous gas loads were observed for all investigated materials. Mineralogical knowledge was used to identify and attribute individual volatile species to reacting, transforming, or decomposing constituents (hydrates, carbonates, sulfates, sulfides, clays, etc.) of the respective regolith simulant in the self-generated gas environment. Cumulative mass losses for individual simulant components as a function of temperature were quantified using mass spectrometry in conjunction with thermogravimetric analysis. Investigation of the four components of CSM-LHT-1G – anorthosite, basalt, augite, and glass – aided the attribution of volatile species to specific compounds and their respective sources. The results showed significant decomposition of non-lunar phases present in the man-made regolith simulants below the typical glass crystallization temperatures, which paves the way to devising methods for enhancing the fidelity of the simulants. Finally, high gas loads and corrosive gases (HF and HCl) were recognized as potential hazards, pertaining to the development of large testbed facilities.

42 ENGINEERING↗
DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2017

High-to-Low Activities across VVI, AMA and PHI

This milestone report documents work performed in CASL that was broadly focused on the use of validated high-fidelity simulation codes to inform, improve and calibrate low-fidelity codes to facilitate multiphysics coupling, design, performance analysis, and risk assessment. This high-to-low (Hi2Lo) initiative has the following objectives: employ physics encapsulated in high-fidelity codes to improve the functionality of low-fidelity codes, quantify biases in low-fidelity codes, develop and calibrate physical models and closure relations so that low-fidelity codes more accurately incorporate requisite physics, and develop low-fidelity codes that can be effectively coupled to simulate multiphysics behavior. In combination, these efforts are designed to impact both CIPS and DNB. For example, the development and experimental design-based Bayesian calibration of dynamic gas conductance models in CTFFuel will provide the capability to better model crud-induced power shifts. Whereas the present emphasis has focused on the high-fidelity codes STAR-CCM+ and BISON and low-fidelity codes CTF and CTFFuel, future emphasis will be expanded to include MAMBA. During the reporting period, Hi2Lo efforts focused on two broad components: demonstration of the experimental design-based Bayesian calibration framework to calibrate CTF using both STAR-generated synthetic data and experimental data, and the use of STAR to inform and improve the turbulence modeling and grid heat transfer modeling capabilities in CTF. A complementary milestone focused on the implementation and verification of fuel models in CTFFuel, for which we demonstrated initial calibration results. Future Hi2Lo work will focus on the use of the experimental design-based Bayesian calibration framework, demonstrated this year for STAR and CTF, to calibrate parameters in the fuel swelling, fuel irradiation-induced densification, and fuel relocation models in CTFFuel using both experimental and BISON-generated data. A second component will focus on the continued use of STAR to improve grid modeling capabilities in CTF.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1989

Atomic oxygen effects on spacecraft materials: The state of the art of our knowledge

In the flight materials exposure data base extensive quantitative data is available from limited exposures in a narrow range of orbital environments. More data is needed in a wider range of environments as well as longer exposure times. Synergistic effects with other environmental factors; polar orbit and higher altitude environments; and real time materials degradation data is needed to understand degradation kinetics and mechanism. Almost no laboratory data exists from high fidelity simulations of the LEO environment. Simulation and test system are under development, and the data base is scanty. Theoretical understanding of hyperthermal atom surface reactions in the LEO environment is not good enough to support development of reliable accelerated test methods. The laser sustained discharge, atom beam sources are the most promising high fidelity simulation-test systems at this time.

Koontz, Steven L.↗
DOE OSTI2024

PeleMP: The Multiphysics Solver for the Combustion Pele Adaptive Mesh Refinement Code Suite

Combustion encompasses multiscale, multiphase reacting flow physics spanning a wide range of scales from the molecular scales, where chemical reactions occur, to the device scales, where the turbulent flow is affected by the geometry of the combustor. This scale disparity and the limited measurement capabilities from experiments make modeling combustion a significant challenge. Recent advancements in high-performance computing (HPC), particularly with the Department of Energy's Exascale Computing Project (ECP), have enabled high-fidelity simulations of practical applications to be performed. The major physics submodels, including chemical reactions, turbulence, sprays, soot, and thermal radiation, exhibit distinctive computational characteristics that need to be examined separately to ensure efficient utilization of computational resources. This paper presents the multiphysics solver for the Pele code suite, called PeleMP, which consists of models for spray, soot, and thermal radiation. Here, the mathematical and algorithmic aspects of the model implementations are described in detail as well as the verification process. The computational performance of these models is benchmarked on multiple supercomputers, including Frontier, an exascale machine. Results are presented from production simulations of a turbulent sooting ethylene flame and a bluff-body swirl stabilized spray flame with sustainable aviation fuels to demonstrate the capability of the Pele codes for modeling practical combustion problems with multiphysics. This work is an important step toward the exascale computing era for high-fidelity combustion simulations providing physical insights and data for predictive modeling of real-world devices.

42 ENGINEERING↗
DOE OSTI2017

Argonne News Brief: Making Sense of Noise

The Argonne Leadership Computing Facility at Argonne National Laboratory helped Joe Nichols, of the University of Minnesota, to create high fidelity simulations of jet turbulence to determine how and where noise is produced. The results may lead to novel engineering designs that reduce noise over commercial flight paths and on aircraft carrier decks.

42 ENGINEERING↗
DOE OSTI2024

GrainGNN: A dynamic graph neural network for predicting 3D grain microstructure

We propose GrainGNN, a surrogate model for the evolution of polycrystalline grain structure under rapid solidification conditions in metal additive manufacturing. High fidelity simulations of solidification microstructures are typically performed using multicomponent partial differential equations (PDEs) with moving interfaces. The inherent randomness of the PDE initial conditions (grain seeds) necessitates ensemble simulations to predict microstructure statistics, e.g., grain size, aspect ratio, and crystallographic orientation. Here, currently such ensemble simulations are prohibitively expensive and surrogates are necessary.In GrainGNN, we use a dynamic graph to represent interface motion and topological changes due to grain coarsening. We use a reduced representation of the microstructure using hand-crafted features; we combine pattern finding and altering graph algorithms with two neural networks, a classifier (for topological changes) and a regressor (for interface motion). Both networks have an encoder-decoder architecture; the encoder has a multi-layer transformer long-short-term-memory architecture; the decoder is a single layer perceptron.We evaluate GrainGNN by comparing it to high-fidelity phase field simulations for in-distribution and out-of-distribution grain configurations for solidification under laser power bed fusion conditions. GrainGNN results in 80%–90% pointwise accuracy; and nearly identical distributions of scalar quantities of interest (QoI) between phase field and GrainGNN simulations compared using Kolmogorov-Smirnov test. GrainGNN's inference speedup (PyTorch on single x86 CPU) over a high-fidelity phase field simulation (CUDA on a single NVIDIA A100 GPU) is 150×–2000× for 100-initial grain problem. Further, using GrainGNN, we model the formation of 11,600 grains in 220 seconds on a single CPU core.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evaluation of the Fitch Wind-Farm Wake Parameterization with Large-Eddy Simulations of Wakes Using the Weather Research and Forecasting Model

Abstract Wind-farm parameterizations in weather models can be used to predict both the power output and farm effects on the flow; however, their correctness has not been thoroughly assessed. We evaluate the wind-farm parameterization of the Weather Research and Forecasting Model with large-eddy simulations (LES) of the wake performed with the same model. We study the impact on the velocity and turbulence kinetic energy (TKE) of inflow velocity, roughness, resolution, number of turbines (one or two), and inversion height and strength. We compare the mesoscale with the LES by spatially averaging the LES within areas correspondent to the mesoscale horizontal spacing: one covering the turbine area and two downwind. We find an excellent agreement of the velocity within the turbine area between the two types of simulations. However, within the same area, we find the largest TKE discrepancies because in mesoscale simulations, the turbine-added TKE has to be highest at the turbine position to be advected downwind. Within the downwind areas, differences between velocities increase as the wake recovers faster in the LES, whereas for the TKE both types of simulations show similar levels. From the various configurations, the impact of inversion height and strength is small for these heights and inversion levels. The highest impact for the one-turbine simulations appears under the low-speed case due to the higher thrust, whereas the impact of resolution is low for the large-eddy simulations but high for the mesoscale simulations. Our findings demonstrate that higher-fidelity simulations are needed to validate wind-farm parameterizations.

17 WIND ENERGY↗
DOE OSTI2021

Initial use of Nek5000/Cardinal to improve closure models in Pronghorn

Heat transfer coefficient closure models for pebble bed reactors are built using a data-driven approach by leveraging the capabilities of an Evolutionary Algorithm entitled Particle Swarm Optimization (PSO). In the present work, the Computational Fluid Dynamics code nekRS was used in order to collect the high-fidelity flow data for a core with 1,568 pebbles. To characterize the heat transfer, multiple concentric regions were considered to extract the physical quantities of interest, e.g./ the Reynolds number. The PSO algorithm is employed as part of an inverse problem targeting determine what are the coefficients for a Nusselt number correlation to match the collected data. Such correlation should follow any given format that is defined a priori. Finally, two correlations are proposed, one with an implicit dependence on the pebbles’ wall temperatures and another expressed as a fully explicit correlation depending on the flow conditions and the position within the core. Anyway, given the generic nature of the proposed approach, correlations following different formats could be tested. Preliminary results for the high-fidelity simulation of a fast MSR core are presented. The target Reynolds number is currently 20K, with the expectation that this will increase, pending the availability of further computational resources. These simulations will be used to inform lower fidelity models, including a coarse CFD turbulence model in Pronghorn. Additionally, they will serve as a reference for the RANS models in Nek5000/NekRS.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1983

Simulation and evaluation of the Sh-2F helicopter in a shipboard environment using the interchangeable cab system

The operation of the SH-2F helicopter from the decks of small ships in adverse weather was simulated using a large amplitude vertical motion simulator, a wide angle computer generated imagery visual system, and an interchangeable cab (ICAB). The simulation facility, the mathematical programs, and the validation method used to ensure simulation fidelity are described. The results show the simulator to be a useful tool in simulating the ship-landing problem. Characteristics of the ICAB system and ways in which the simulation can be improved are presented.

Paulk, C. H., Jr.↗