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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 199 records · Page 11

Combining On-Line Characterization Tools with Modern Software Environments for Optimal Operation of Polymerization Processes

Here, this paper discusses the initial steps towards the formulation and implementation of a generic and flexible model centric framework for integrated simulation, estimation, optimization and feedback control of polymerization processes. For the first time it combines the powerful capabilities of the automatic continuous on-line monitoring of polymerization system (ACOMP), with a modern simulation, estimation and optimization software environment towards an integrated scheme for the optimal operation of polymeric processes. An initial validation of the framework was performed for modelling and optimization using literature data, illustrating the flexibility of the method to apply under different systems and conditions. Subsequently, off-line capabilities of the system were fully tested experimentally for model validations, parameter estimation and process optimization using ACOMP data. Experimental results are provided for free radical solution polymerization of methyl methacrylate.

42 ENGINEERING↗

INtegrated Fluid & paRticles simulatioN cOde (INF&RNO) v1.0

INF&RNO (INtegrated Fluid & paRticle simulation cOde) is a 2D cylindrical (r-z) code to model the interaction of short laser pulse(s) with an underdense plasma. The code is based on an envelope model for the laser field, and the action of the laser on the plasma is modeled with the time-averaged ponderomotive force approximation. The code features an improved laser envelope solver which enables an accurate description of the laser pulse evolution deep into depletion even at a reasonably low resolution.

Benedetti, Carlo [Lawrence Berkeley National Labor↗

Integrated Modeling and Simulation Capability For Full Scale Multi-Physics Simulation and Visualization of Microreactor Concept

Microreactors are small mobile transportable nuclear reactors with thermal power less than 20 MWt that are designed to meet the needs of remote areas, military installations, emergency operations, and disaster relief zones. These reactor are concepts that are intended to be factory-manufacturable, easily transportable, and will allow for semi- or full-autonomous operation. To assist with development of microreactors, modeling and experimentation need to be performed with verification and validation to gain confidence in the models and tools. The objective of this study is apply advanced modeling and simulation capabilities being developed by the DOE Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to perform integrated modeling and simulation capability for multiphysics simulation of the microreactor concepts. This activity will provide an opportunity to exercise the codes to provide both gain experience and to provide feedback to the developers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Accelerated path integral methods for atomistic simulations at ultra-low temperatures

Path integral methods provide a rigorous and systematically convergent framework to include the quantum mechanical nature of atomic nuclei in the evaluation of the equilibrium properties of molecules, liquids, or solids at finite temperature. Such nuclear quantum effects are often significant for light nuclei already at room temperature, but become crucial at cryogenic temperatures such as those provided by superfluid helium as a solvent. Unfortunately, the cost of converged path integral simulations increases significantly upon lowering the temperature so that the computational burden of simulating matter at the typical superfluid helium temperatures becomes prohibitive. Here we investigate how accelerated path integral techniques based on colored noise generalized Langevin equations, in particular the so-called path integral generalized Langevin equation thermostat (PIGLET) variant, perform in this extreme quantum regime using as an example the quasi-rigid methane molecule and its highly fluxional protonated cousin, CH{sub 5}{sup +}. We show that the PIGLET technique gives a speedup of two orders of magnitude in the evaluation of structural observables and quantum kinetic energy at ultralow temperatures. Moreover, we computed the spatial spread of the quantum nuclei in CH{sub 4} to illustrate the limits of using such colored noise thermostats close to the many body quantum ground state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Path Integral Monte Carlo Simulations of Warm Dense Matter and Plasmas

New path integral Monte Carlo simulation (PIMC) techniques will be developed and applied to derive the equation of state (EOS) for the regime of warm dense matter and dense plasmas where existing first-principles methods cannot be applied. While standard density functional theory has been used to accurately predict the structure of many solids and liquids up to temperatures on the order of 10,000 K, this method is not applicable at much higher temperature where electronic excitations become important because the number of partially occupied electronic orbitals reaches intractably large numbers and, more importantly, the use of zero-temperature exchange-correlation functionals introduces an uncontrolled approximation. Here we focus on PIMC methods that become more and more efficient with increasing temperatures and still include all electronic correlation effects. In this approach, electronic excitations increase the efficiency rather than reduce it. While it has commonly been assumed such methods can only be applied to elements without core electrons like hydrogen and helium, we recently showed how to extend PIMC to heavier elements by performing the first PIMC simulations of carbon and water plasmas [Driver, Militzer, Phys. Rev. Lett. 108 (2012) 115502]. Here we propose to continue this important development to extend the reach of PIMC simulations to yet heavier elements and also lower temperatures. The goal is to provide a robust first-principles simulation method that can accurately and efficiently study materials with excited electrons at solid-state densities in order to access parts of the phase diagram such the regime of warm dense matter and plasmas where so far only more approximate, semi-analytical methods could be applied.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Using AI Simulations to Dynamically Model Multi-agent Multi-team Energy Systems

The complexity of energy systems is well known as they are complex and intricate systems. As a result, many extant studies have used many simplifications or generalizations that do not accurately reflect the nature of this complex system. In particular, most HVAC systems are modeled as a single unit, or several large units, rather than as a hierarchical composite (e.g., as a floor rather than as a collection of disparate rooms). The net result of this is that the simulations are too generic to perform meaningful analysis, machine learning, or integrated simulation. We propose using a multi-agent multi-team strategic simulations framework called SiMAMT to better define, model, simulate, and learn the HVAC environment. SiMAMT allows us to create distinct models for each type of room, hierarchically aggregate them into units (like floors, or sections), and then into larger sets (like buildings or a campus), and then perform a simulation that interacts with each sub-element individually, the teams of sub-elements collectively, and the entire set in aggregation. Further, and most importantly, we additionally model another ‘team’ within the simulation framework - the users of the systems. Again, each individual is modeled distinctly, aggregated into sub-sets, then collected into large sets. Each user, or agent, is performing on their own but with respect to the larger team goals. This provides a simulation that has a much higher model fidelity and more applicable results that match the real-world.

Franklin, D. Michael↗

Airspace Technology Demonstration 2 (ATD-2) Integrated Surface and Airspace Simulation - Experiment Plan

This presentation describes the objectives and high level setup for the human-in-the-loop simulation of the integrated surface and airsapce simulation of the ATD-2 Integrated Arrival, Departure, Surface (IADS) system. The purpose of the simulation is to evaluate the functionality of the IADS system, including tactical surface scheduler, negotiation of departure times for the flights under Traffic Management Initiatives (TMIs), and data exchange between ATC Tower and airline Ramp. The same presentation was presented to serve the experiment review prior to the simulation.

Surface↗

Estimating the Likelihood of GHG Concentration Scenarios From Probabilistic Integrated Assessment Model Simulations

The climate scenarios that form the basis for current climate risk assessments have no assigned probabilities, and this impedes the analysis of future climate risks. This paper proposes an approach to estimate the probability of carbon dioxide (CO 2 ) concentration scenarios used in key climate change modeling experiments. It computes the CO 2 emissions compatible with the concentrations prescribed by Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6 experiments. The distribution of these compatible cumulative emissions is interpreted as the likelihood of future emissions given a concentration pathway. Using Bayesian analysis, the probability of each pathway can be estimated from a probabilistic sample of future emissions. The approach is demonstrated with five probabilistic CO 2 emission simulation ensembles from four Integrated Assessment Models (IAM), leading to independent estimates of the likelihood of the CO 2 concentration of Representative Concentration Pathways (RCP) and Shared Socioeconomic Pathways (SSP). Results suggest that SSP5-8.5 is unlikely for the second half of the 21st century, but offer no clear consensus on which of the remaining scenarios is most likely. Estimates of likelihoods of CO 2 concentrations associated with RCP and SSP scenarios are affected by sampling errors, differences in emission sources simulated by the IAMs, and a lack of a common experimental framework for IAM simulations. These shortcomings, along with a small IAM ensemble size, limit the applicability of the results presented here. Novel joint IAM and the Earth System Model experiments are needed to deliver actionable probabilistic climate risk assessments.

54 ENVIRONMENTAL SCIENCES↗

Simulation Technology at NASA

NASA Ames Research Center is home to several high-fidelity research flight and air-traffic control simulation facilities which, together with an experienced workforce, produce high-quality research data and findings that have proven to be applicable in the real world. These assets include the Vertical Motion Simulator (VMS), Crew Vehicle Systems Research Facility (CVSRF), Future Flight Central (FFC) air traffic control tower simulator, and several air-traffic control (ATC) simulators. The VMS combines a high-fidelity simulation capability with an adaptable simulation environment, enabling customization for numerous human-in-the-loop research applications. The distinctive feature of the VMS is its unparalleled large amplitude, high-fidelity motion capability. In over 30 years of continuous operation, the VMS has contributed significantly to the body of knowledge in a range of disciplines directly benefiting several aerospace programs and flight safety, including the design and development of flight control systems for the Joint Strike Fighter, Space Shuttle Orbiter, and rotorcraft. It continues to be used for researching new vehicle configurations, vehicle control and safety, transfer-of-training, etc., by NASA, other government agencies, and Industry.The CVSRF includes two motion-based flight simulators: a Boeing 747-400 full flight simulator and the reconfigurable Advanced Concepts Flight Simulator (ACFS). These simulators are primarily used to research air-traffic management concepts and procedures, advanced navigation and avionics concepts, and cockpit human factors. FFC is a full-sized control tower simulator with a 360-degree external field-of-view display system and reconfigurable system architecture. FFC and the ATC simulators are used for testing air-traffic management automation and decision support tools and demonstrate their feasibility in a realistic environment prior to technology transfer for implementation in the National Airspace System (NAS).To support integrated simulations and flight-tests for NASA's Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) Project, NASA developed a distributed test environment incorporating Live, Virtual, Constructive, (LVC) concepts. Development of the software enabling the LVC is conducted primarily at the Distributed Simulation Research Lab (DSRL) at NASA Ames. The LVC components provide the core infrastructure supporting simulation of UAS operations by integrating live and virtual aircraft in a realistic air traffic environment. This provides the ability to conduct tests more efficiently by promoting the use of existing distributed assets. The LVC infrastructure was used in several human-in-the-loop simulations to evaluate acceptance of Detect and Avoid (DAA) advisories used by UAS pilots to maintain well clear of other virtual traffic and to negotiate maneuvers with air traffic control. It is currently being used to support testing of self-separation algorithms between unmanned and manned aircraft in live flight. Further simulations with more comprehensive air traffic scenarios mixing live and virtual aircraft is planned.In the current fiscal environment, maintaining and upgrading these high-fidelity simulation assets and retaining the skilled workforce necessary to meet future research needs is the primary non-technical challenge.

CVSRF↗

Solving iTOUGH2 simulation and optimization problems using the PEST protocol

The PEST protocol has been implemented into the iTOUGH2 code, allowing the user to link any simulation program (with ASCII-based inputs and outputs) to iTOUGH2's sensitivity analysis, inverse modeling, and uncertainty quantification capabilities. These application models can be pre- or post-processors of the TOUGH2 non-isothermal multiphase flow and transport simulator, or programs that are unrelated to the TOUGH suite of codes. PEST-style template and instruction files are used, respectively, to pass input parameters updated by the iTOUGH2 optimization routines to the model, and to retrieve the model-calculated values that correspond to observable variables. We summarize the iTOUGH2 capabilities and demonstrate the flexibility added by the PEST protocol for the solution of a variety of simulation-optimization problems. In particular, the combination of loosely coupled and tightly integrated simulation and optimization routines provides both the flexibility and control needed to solve challenging inversion problems for the analysis of multiphase subsurface flow and transport systems.

54 ENVIRONMENTAL SCIENCES↗

Simulation verification techniques study: Simulation performance validation techniques document

Techniques and support software for the efficient performance of simulation validation are discussed. Overall validation software structure, the performance of validation at various levels of simulation integration, guidelines for check case formulation, methods for real time acquisition and formatting of data from an all up operational simulator, and methods and criteria for comparison and evaluation of simulation data are included. Vehicle subsystems modules, module integration, special test requirements, and reference data formats are also described.

Duncan, L. M.↗

Integration of CELSS Simulation with Long-Term Crop Scheduling

This project presents guidelines for the integration of the Intelligent Crop Scheduler (ICS) developed by Leon (1995) with a version of the Biological Life Support System (BLSS) simulation based on the work by Volk and Rummel (1987). These guidelines will also aid in defining the appropriate model detail of simulation-based schedulers. ICS determines what, when and how much to plant of different crops. These decisions are made such that the critical reservoir levels are maintained close to their nominal or desired settings during the duration of the mission. Initial feasibility of the approach has been demonstrated using simplified implementations of the scheduling approach and CELSS 'world' model developed by the investigator at JSC in the Summer of 1995. The BLSS model incorporates more detail. The increased fidelity is in terms of added mass-regeneration formalism (biochemical stoichiometry), more plants, and more accurate modeling of the mechanical system. This report describes the main features of the Crop scheduler and CELSS simulator, discusses integration issues, and provides with detailed guidelines for the integration of these two applications.

Leon, V. Jorge↗

Human Systems Integration: Requirements and Functional Decomposition

This deliverable was intended as an input to the Access 5 Policy and Simulation Integrated Product Teams. This document contains high-level pilot functionality for operations in the National Airspace System above FL430. Based on the derived pilot functions the associated pilot information and control requirements are given.

Berson, Barry↗

Numerical simulation of the integrated space shuttle vehicle in ascent

A simulation of the flow about the integrated space shuttle vehicle in ascent mode has been undertaken for various flight conditions using the Chimera composite grid discretization approach. Overset body-conforming grids were used to represent each geometric component, and an implicit approximately factored finite-difference procedure was used to solve the three-dimensional thin-layer Navier-Stokes equations. The computational results have been compared with both wind tunnel and flight test data. Although relatively good agreement is obtained with the experimental data, further refinement and evaluation of numerical error is under way.

Buning, P. G.↗

Informing nuclear physics via machine learning methods with differential and integral experiments

Information from differential nuclear-physics experiments and theory is often too uncertain to accurately define nuclear-physics observables such as cross sections or energy spectra. Integral experimental data, representing the applications of these observables, are often more precise but depend simultaneously on too many of them to unambiguously identify issues in the observable with human expert analysis alone. Here, we explore how we can leverage physics knowledge gained from differential experimental data, nuclear theory, integral experiments, and neutron-transport calculations to better understand nuclear-physics observables in the context of the application area represented by integral experiments. We support this task with machine-learning methods to discern trends in a large amount of convoluted data. Differential and integral information was used in an analysis augmented by the random forest and the Shapley additive explanations metric. We chose as an application area one that is represented by criticality measurements and pulsed-sphere neutron-leakage spectra. We show one representative example ( 241 Pu fission observables) where the combination of differential and integral information allowed to resolve issues in data representing these observables. As a starting point, the machine learning (ML) algorithms highlighted several observables as leading potentially to bias in simulating integral experiments. Differential information, paired with sensitivity to integral quantities, allowed us then to pinpoint one specific observable ( 241 Pu fission cross section) as the main driver of bias. The comparison to integral experiments, on the other hand, allowed us to indicate a likely reliable experiment among several discrepant ones for this observables. In other cases (e.g., 239 Pu observables), we were not able to resolve the confounding introduced by integral experiments but instead highlighted the need for targeted new experiments and theory developments to better constrain the nuclear-physics space for the application area represented by integral experiments. We were able to combine information from differential experimental data, nuclear-physics theory, integral experiments, and neutron-transport simulations of the latter experiments with the help of the random forest algorithm and expert judgment. This combination of knowledge allows to improve our description of nuclear-physics observables as applied to a particular application area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modelling I and C systems with relays for simulation, adapting CIM standards - 243

As the nuclear power plants are in operation for many years, a main issue is to integrate simulation activities in parallel to the present I and C design process in order to limit impacts on current operating I and C engineering process and commissioning activities. The objective is to keep the existing I and C data and diagrams format. EDF chose to build an intermediate file independent of the tool used for simulation to exchange and store data. This file has been created adapting CIM standards (IEC 61968-13 and IEC 61970-301). It is an XML file built according to an RDF schema. CIM standards are intended to model transport or distribution electrical networks and used to facilitate system integration and information exchanges. We chose to adapt CIM to model EDF electromechanical relay circuitries in order to re-use all methods and tools developed around CIM standards such as RDF schema and RiseClipse, an open source tool developed by EDF and SUPELEC engineering school that will be used to verify exported I and C data according to a data model and to EDF engineering rules. This paper will describe the ongoing project on simulation in parallel to current I and C design process, focusing on how I and C electromechanical relays data are modelled based on CIM standards, and what benefits that model provides to I and C Verification and Validation activities. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

HOMER Economic Models - US Navy

This LETTER REPORT has been prepared by Idaho National Laboratory for US Navy NAVFAC EXWC to support in testing pre-commercial SIREN (Simulated Integration of Renewable Energy Networks) computer software models. In the logistics mode SIREN software simulates the combination of renewable power sources (solar arrays, wind turbines, and energy storage systems) in supplying an electrical demand. NAVFAC EXWC will create SIREN software logistics models of existing or planned renewable energy projects at five Navy locations (San Nicolas Island, AUTEC, New London, & China Lake), and INL will deliver additional HOMER computer models for comparative analysis. In the transient mode SIREN simulates the short time-scale variation of electrical parameters when a power outage or other destabilizing event occurs. In the HOMER model, a variety of inputs are entered such as location coordinates, Generators, PV arrays, Wind Turbines, Batteries, Converters, Grid costs/usage, Solar resources, Wind resources, Temperatures, Fuels, and Electric Loads. HOMER's optimization and sensitivity analysis algorithms then evaluate the economic and technical feasibility of these technology options and account for variations in technology costs, electric load, and energy resource availability. The Navy can then use HOMER’s optimization and sensitivity results to compare to those of the SIREN model. The U.S. Department of Energy (DOE) Idaho National Laboratory (INL) possesses unique expertise and experience in the software, hardware, and systems design for the integration of renewable energy into the electrical grid. NAVFAC EXWC will draw upon this expertise to complete mission requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗