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At least 37 records · Page 2

Concurrent processing simulation of the space station

The development of a new capability for the time-domain simulation of multibody dynamic systems and its application to the study of a large angle rotational maneuvers of the Space Station is described. The effort was divided into three sequential tasks, which required significant advancements of the state-of-the art to accomplish. These were: (1) the development of an explicit mathematical model via symbol manipulation of a flexible, multibody dynamic system; (2) the development of a methodology for balancing the computational load of an explicit mathematical model for concurrent processing; and (3) the implementation and successful simulation of the above on a prototype Custom Architectured Parallel Processing System (CAPPS) containing eight processors. The throughput rate achieved by the CAPPS operating at only 70 percent efficiency, was 3.9 times greater than that obtained sequentially by the IBM 3090 supercomputer simulating the same problem. More significantly, analysis of the results leads to the conclusion that the relative cost effectiveness of concurrent vs. sequential digital computation will grow substantially as the computational load is increased. This is a welcomed development in an era when very complex and cumbersome mathematical models of large space vehicles must be used as substitutes for full scale testing which has become impractical.

Gluck, R.

Simulation Process Automation for Window Attachments Rating

WINDOW (LBNL 2022) and AERCalc (LBNL 2018) software developed by Lawrence Berkely National Laboratory are needed for running the tool. The database that in installed along with WINDOW software is utilized and modified to develop database for AERCalc simulation in generic case. However, any other custom WINDOW database created by users can be utilized as well. Another requirement for use of the tool is the availability of the shading fabric in the complex glazing database (CGDB). The CGDB id of the fabric was used for database generation discussed in next section.

97 MATHEMATICS AND COMPUTING

Validation Data for Benchmarking Wire Arc Additive Manufacturing Process Simulations

Residual stresses cause geometric distortion and affect mechanical performance of additively manufactured structures, yet they are notoriously difficult to assess and predict. Distortion (warpage) can drive parts outside dimensional tolerance limits, leading to part rejection or rework. For parts that meet tolerance, locked-in residual stress fields can affect structural integrity during operation, particularly subcritical cracking by fatigue, creep, or corrosion. This work develops benchmark data for a common additive manufacturing process (Wire Arc Additive Manufacturing) that can be applied for calibration and validation of physical process models that predict residual stress fields. The work includes design of two different samples of differing geometry, detailed manufacturing records for a set of physical samples, and an extensive set of residual stress measurement data developed using two diverse techniques (the contour method and neutron diffraction). An initial application of the work is also reported, where a modeling challenge was issued to secure residual stress model predictions from two independent laboratories that were blind to residual stress measurement data. These initial blind residual stress predictions show significant discrepancies relative to the measurement data, illustrating the potential value of the underlying validation data. An open repository for this work, including the sample designs, manufacturing process records, and the residual stress data, is also provided for future application in non-blind validation efforts.

36 MATERIALS SCIENCE

Verification of a three-dimensional resin transfer molding process simulation model

Experimental evidence was obtained to complete the verification of the parameters needed for input to a three-dimensional finite element model simulating the resin flow and cure through an orthotropic fabric preform. The material characterizations completed include resin kinetics and viscosity models, as well as preform permeability and compaction models. The steady-state and advancing front permeability measurement methods are compared. The results indicate that both methods yield similar permeabilities for a plain weave, bi-axial fiberglass fabric. Also, a method to determine principal directions and permeabilities is discussed and results are shown for a multi-axial warp knit preform. The flow of resin through a blade-stiffened preform was modeled and experiments were completed to verify the results. The predicted inlet pressure was approximately 65% of the measured value. A parametric study was performed to explain differences in measured and predicted flow front advancement and inlet pressures. Furthermore, PR-500 epoxy resin/IM7 8HS carbon fabric flat panels were fabricated by the Resin Transfer Molding process. Tests were completed utilizing both perimeter injection and center-port injection as resin inlet boundary conditions. The mold was instrumented with FDEMS sensors, pressure transducers, and thermocouples to monitor the process conditions. Results include a comparison of predicted and measured inlet pressures and flow front position. For the perimeter injection case, the measured inlet pressure and flow front results compared well to the predicted results. The results of the center-port injection case showed that the predicted inlet pressure was approximately 50% of the measured inlet pressure. Also, measured flow front position data did not agree well with the predicted results. Possible reasons for error include fiber deformation at the resin inlet and a lag in FDEMS sensor wet-out due to low mold pressures.

Fingerson, John C.

Modeling and optimization of a regenerative fuel cell system using the ASPEN process simulator

The Hydrogen-Oxygen Regenerative Fuel Cell System was identified as a key component for energy storage in support of future lunar missions. Since the H2-O2 regenerative electrochemical conversion technology has not yet been tested in space applications, it is necessary to implement predictive techniques to develop initial feasible system designs. The ASPEN simulation software furnishes a constructive medium for analyzing and for optimizing such systems. A rudimentary regenerative fuel cell system design was examined using the ASPEN simulator and this modular approach allows for easy addition of supplementary ancillary components and easy integration with life support systems. The modules included in the preliminary analyses may serve as the fundamental structure for more complicated energy storage systems.

Maloney, Thomas M.

Modeling and optimization of a regenerative fuel cell system using the ASPEN process simulator

The Hydrogen-Oxygen Regenerative Fuel Cell System was identified as a key component for energy storage in support of future lunar missions. Since the H2-O2 regenerative electrochemical conversion technology has not yet been tested in space applications, it is necessary to implement predictive techniques to develop initial feasible system designs. The ASPEN simulation software furnishes a constructive medium for analyzing and optimizing such systems. A rudimentary regenerative fuel cell system design was examined using the ASPEN simulator and this modular approach allows for easy addition of supplementary ancillary components and easy integration with life support systems. The modules included in the preliminary analyses may serve as the fundamental structure for more complicated energy storage systems.

Maloney, Thomas M.

The Future of Electronic Device Design: Device and Process Simulation Find Intelligence on the World Wide Web

We are on the path to meet the major challenges ahead for TCAD (technology computer aided design). The emerging computational grid will ultimately solve the challenge of limited computational power. The Modular TCAD Framework will solve the TCAD software challenge once TCAD software developers realize that there is no other way to meet industry's needs. The modular TCAD framework (MTF) also provides the ideal platform for solving the TCAD model challenge by rapid implementation of models in a partial differential solver.

Biegel, Bryan A.

SNAP: Simulating New Acquisition Processes

Simulation models of acquisition processes range in scope from isolated applications to the 'Big Picture' captured by SNAP technology. SNAP integrates a family of models to portray the full scope of acquisition planning and management activities, including budgeting, scheduling, testing and risk analysis. SNAP replicates the dynamic management processes that underlie design, production and life-cycle support. SNAP provides the unique 'Big Picture' capability needed to simulate the entire acquisition process and explore the 'what-if' tradeoffs and consequences of alternative policies and decisions. Comparison of cost, schedule and performance tradeoffs help managers choose the lowest-risk, highest payoff at each step in the acquisition process.

Alfeld, Louis E.

On the normality and accuracy of simulated random processes.

Efficient methods of simulating stationary and nonstationary random processes and envelopes, by using a series of sine or cosine functions or by using the fast Fourier transform, have been proposed previously. Without applying the central limit theorem, it is shown in this paper that the simulated random processes are asymptotically Gaussian processes as the number of terms, N, of sine or cosine functions approaches infinity. The accuracy of the first-order probability densities of the simulated random processes is investigated by using the fast Fourier transform. Numerical results are computed with respect to the variation of the number of terms, N, of sine or cosine functions used for simulation. It is shown that within the practical range of N, such as 500, the accuracy is remarkably satisfactory even outside the region of 3 standard deviations.

Yang, J.-N.

Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi‐Member and Stochastic Parameterizations

Abstract Deep learning is a powerful tool to represent subgrid processes in climate models, but many application cases have so far used idealized settings and deterministic approaches. Here, we develop stochastic parameterizations with calibrated uncertainty quantification to learn subgrid convective and turbulent processes and surface radiative fluxes of a superparameterization embedded in an Earth System Model (ESM). We explore three methods to construct stochastic parameterizations: (a) a single Deep Neural Network (DNN) with Monte Carlo Dropout; (b) a multi‐member parameterization; and (c) a Variational Encoder Decoder with latent space perturbation. We show that the multi‐member parameterization improves the representation of convective processes, especially in the planetary boundary layer, compared to individual DNNs. The respective uncertainty quantification illustrates that methods (b) and (c) are advantageous compared to a dropout‐based DNN parameterization regarding the spread of convective processes. Hybrid simulations with our best‐performing multi‐member parameterizations remained challenging and crash within the first days. Therefore, we develop a pragmatic partial coupling strategy relying on the superparameterization for condensate emulation. Partial coupling reduces the computational efficiency of hybrid Earth‐like simulations but enables model stability over 5 months with our multi‐member parameterizations. However, our hybrid simulations exhibit biases in thermodynamic fields and differences in precipitation patterns. Despite this, the multi‐member parameterizations enable improvements in reproducing tropical extreme precipitation compared to a traditional convection parameterization. Despite these challenges, our results indicate the potential of a new generation of multi‐member machine learning parameterizations leveraging uncertainty quantification to improve the representation of stochasticity of subgrid effects.

Behrens, Gunnar [Deutsches Zentrum für Luft‐ und R

Anvil Glaciation in a Deep Cumulus Updraught over Florida Simulated with the Explicit Microphysics Model. I: Impact of Various Nucleation Processes

Simulations of a cumulonimbus cloud observed in the Cirrus regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) with an advanced version of the Explicit Microphysics Model (EMM) are presented. The EMM has size-resolved aerosols and predicts the time evolution of sizes, bulk densities and axial ratios of ice particles. Observations by multiple aircraft in the troposphere provide inputs to the model, including observations of the ice nuclei and of the entire size distribution of condensation nuclei. Homogeneous droplet freezing is found to be the source of almost all of the ice crystals in the anvil updraught of this particular model cloud. Most of the simulated droplets that freeze to form anvil crystals appear to be nucleated by activation of aerosols far above cloud base in the interior of the cloud ("secondary" or "in cloud" droplet nucleation). This is partly because primary droplets formed at cloud base are invariably depleted by accretion before they can reach the anvil base in the updraught, which promotes an increase with height of the average supersaturation in the updraught aloft. More than half of these aerosols, activated far above cloud base, are entrained into the updraught of this model cloud from the lateral environment above about 5 km above mean sea level. This confirms the importance of remote sources of atmospheric aerosol for anvil glaciation. Other nucleation processes impinge indirectly upon the anvil glaciation by modifying the concentration of supercooled droplets in the upper levels of the mixed-phase region. For instance, the warm-rain process produces a massive indirect impact on the anvil crystal concentration, because it determines the mass of precipitation forming in the updraught. It competes with homogeneous freezing as a sink for cloud droplets. The effects from turbulent enhancement of the warm-rain process and from the nucleation processes on the anvil ice properties are assessed.

Phillips, Vaughan T. J.

Evaluating the Credibility of Transport Processes in Simulations of Ozone Recovery using the Global Modeling Initiative Three-dimensional Model

The Global Modeling Initiative (GMI) has integrated two 36-year simulations of an ozone recovery scenario with an offline chemistry and tra nsport model using two different meteorological inputs. Physically ba sed diagnostics, derived from satellite and aircraft data sets, are d escribed and then used to evaluate the realism of temperature and transport processes in the simulations. Processes evaluated include barri er formation in the subtropics and polar regions, and extratropical w ave-driven transport. Some diagnostics are especially relevant to sim ulation of lower stratospheric ozone, but most are applicable to any stratospheric simulation. The global temperature evaluation, which is relevant to gas phase chemical reactions, showed that both sets of me teorological fields have near climatological values at all latitudes and seasons at 30 hPa and below. Both simulations showed weakness in upper stratospheric wave driving. The simulation using input from a g eneral circulation model (GMI(GCM)) showed a very good residual circulation in the tropics and Northern Hemisphere. The simulation with inp ut from a data assimilation system (GMI(DAS)) performed better in the midlatitudes than it did at high latitudes. Neither simulation forms a realistic barrier at the vortex edge, leading to uncertainty in the fate of ozone-depleted vortex air. Overall, tracer transport in the offline GML(GCM) has greater fidelity throughout the stratosphere tha n it does in the GMI(DAS)

Strahan, Susan E.

Dynamic Modeling of Process Technologies for Closed-Loop Water Recovery Systems

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents dynamic simulations of chemical process for primary processor technologies including: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system, the Wiped-Film Rotating Disk (WFRD), and post-distillation water polishing processes such as the Volatiles Removal Assembly (VRA) that were developed using the Aspen Custom Modeler and Aspen Plus process simulation tools. The results expand upon previous work for water recovery technology models and emphasize dynamic process modeling and results. The paper discusses system design, modeling details, and model results for each technology and presents some comparisons between the model results and available test data. Following these initial comparisons, some general conclusions and forward work are discussed.

Allada, Rama Kumar

Dynamic Modeling of Process Technologies for Closed-Loop Water Recovery Systems

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents dynamic simulations of chemical process for primary processor technologies including: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system, the Wiped-Film Rotating Disk (WFRD), and post-distillation water polishing processes such as the Volatiles Removal Assembly (VRA). These dynamic models were developed using the Aspen Custom Modeler (Registered TradeMark) and Aspen Plus(Registered TradeMark) process simulation tools. The results expand upon previous work for water recovery technology models and emphasize dynamic process modeling and results. The paper discusses system design, modeling details, and model results for each technology and presents some comparisons between the model results and available test data. Following these initial comparisons, some general conclusions and forward work are discussed.

Allada, Rama Kumar

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO2 Fluxes Upon Soil Warming

Abstract Understanding factors influencing carbon effluxes from soils to the atmosphere is important in a world experiencing climatic change. Two important uncertainties related to soil organic carbon (SOC) stock responses to a changing climate are (a) whether soil microbial communities acclimate or adapt to changes in soil temperature and (b) how to represent this process in SOC models. To further explore these issues, we included thermal adaptation of enzyme‐mediated processes in a mechanistic SOC model (ReSOM) using the macromolecular rate theory. Thermal adaptation is defined here to encompass all potential responses of soil microbes and microbial communities following a change in temperature. To assess the effects of thermal adaptation of enzyme‐mediated processes on simulated SOC losses, ReSOM was applied to data collected from a 13‐year soil warming experiment. Results show that a model omitting thermal adaptation of enzyme‐mediated processes substantially overestimates observed CO 2 effluxes during the initial years of soil warming. The bias against observed CO 2 effluxes was lower for models including thermal adaptation of enzyme‐mediated processes. In addition, for a simulated linear 3°C soil warming over 100 years, models including thermal adaptation of enzyme‐mediated processes simulated SOC losses of a factor of three smaller than models omitting this process. As thermal adaptation of microbial community characteristics is generally not included in models simulating feedback between the soil, biosphere and atmosphere, we encourage future studies to assess the potential impact that microbial adaptation has on soil carbon – climate feedback representations in models. Plain Language Summary A major uncertainty in projecting how much soil organic carbon (SOC) will be converted to CO 2 as a consequence of climate change is related to how soil microbes may adapt to increasing soil temperatures. While this “microbial thermal adaptation” has been shown to occur in short‐term lab incubation experiments, its effect on SOC cycling on a decadal timescale is not clear. To address this knowledge gap, a mechanistic SOC model was used to simulate data collected from a 13‐year soil warming experiment, to assess how microbial thermal adaptation affects predicted SOC losses upon soil warming. The model results show that incorporating microbial thermal adaptation into the model led to reduced CO 2 effluxes from the soil to the atmosphere compared to the common approach of omitting this mechanism. Our results imply that projected SOC losses for the decades to come may be reduced when this mechanism is incorporated in land models. We therefore advocate for more research on the mechanisms controlling microbial thermal adaptation, and how to implement this mechanism in SOC models. Key Points A crucial aspect of soil organic carbon (SOC) models is the representation of soil microbes Predicted soil CO 2 fluxes upon soil warming are reduced when accounting for microbial thermal adaptation On a centennial time scale, this thermal adaptation results in up to a factor of three lower predicted SOC loss

Van de Broek, Marijn

Geomechanical models of impact cratering: Puchezh-Katunki structure

Impact cratering is a complex natural phenomenon that involves various physical and mechanical processes. Simulating these processes may be improved using the data obtained during the deep drilling at the central mound of the Puchezh-Katunki impact structure. A research deep drillhole (named Vorotilovskaya) has been drilled in the Puchezh-Katunki impact structure (European Russia, 57 deg 06 min N, 43 deg 35 min E). The age of the structure is estimated at about 180 to 200 m.y. The initial rim crater diameter is estimated at about 40 km. The central uplift is composed of large blocks of crystalline basement rocks. Preliminary study of the core shows that crystalline rocks are shock metamorphosed by shock pressure from 45 GPa near the surface to 15-20 GPa at a depth of about 5 km. The drill core allows the possibility of investigating many previously poorly studied cratering processes in the central part of the impact structure. As a first step one can use the estimates of energy for the homogeneous rock target. The diameter of the crater rim may be estimated as 40 km. The models elaborated earlier show that such a crater may be formed after collapse of a transient cavity with a radius of 10 km. The most probable range of impact velocities from 11.2 to 30 km/s may be inferred for the asteroidal impactor. For the density of a projectile of 2 g/cu cm the energy of the impact is estimated as 1E28 to 3E28 erg. In the case of vertical impact, the diameter of an asteroidal projectile is from 1.5 to 3 km for the velocity range from 11 to 30 km/s. For the most probable impact angle of 45 deg, the estimated diameter of an asteroid is slightly larger: from 2 to 4 km. Numerical simulation of the transient crater collapse has been done using several models of rock rheology during collapse. Results show that the column at the final position beneath the central mound is about 5 km in length. This value is close to the shock-pressure decay observed along the drill core. Further improvement of the model needs to take into account the blocky structure of target rocks revealed by drilling.

Ivanov, B. A.