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DOE OSTI2017

Development of Fusion Neutronics Methodology, Software, and Testing Facility in FDS Team

Fusion neutronics including methodology, software, experiments, etc. is studied concerning the generation, utilizing and protection of neutrons in fusion facilities. Achievements have been made in the past decades to solve the new problems fusion neutronics. However there is still some way to go such as following. Automatic modeling method based on CAD has been developed to avoid the heavy burden of manual geometry description. The pre-processing costs much time to simplify the CAD model for converting to Constructive Solid Geometry (CSG), 2D or 3D mesh based geometry. This problem has become a new focus. Deep penetration of radiation shielding is notable problem for fusion. Adaptive variance reduction methods such as Consistent Adjoint Driven Importance Sampling (CADIS) were developed to accelerate convergence. However the gap still exists between engineering requirements and current methodology. The geometry simplification, homogenizing based tally, error in nuclear data and error propagation in coupled calculation, etc., causes considerable uncertainty, which leads to 'safety factor' applied in simulation results to achieve required safety margin. It can significantly raise the cost and even makes it impractical to initiate the fusion facilities. Uncertainty qualification, error analysis and error propagation problem should be studied. New methodology and software should be validated. For example the (n,p), (n,a), (n,t) cross section of Cu, Fe, W, Ni which is important for evaluation of material radiation damage is absent. The validation of neutronics properties of special components such as first wall, blanket and coil are needed. The D-T fusion neutron generator can directly represent the neutron environment in fusion reactors. However the neutron yield is several orders of magnitudes lower than requirements. To resolve obstacles in fusion neutronics, broad improvements of methodology, software and testing facility have been achieved by FDS Team in recent years and the main progress was introduced in this paper.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

An efficient Bayesian inversion of a geothermal prospect using a multivariate adaptive regression spline method

In this study, an efficient Bayesian framework equipped with a multivariate adaptive regression spline (MARS) technique is developed to alleviate computational burdens encountered in a conventional Bayesian inversion of a geothermal prospect. Fast MARS models are developed from training dataset generated by CPU-intensive hydrothermal models and used as surrogate of high-fidelity physical models in Markov Chain Monte Carlo (MCMC) sampling. This Bayesian inference with MARS-enabled MCMC method is used to reduce prior estimates of uncertainty in structural or characteristic hydrothermal flow parameters of the model to posterior distributions. A geothermal prospect near Superstition Mountain in Imperial County of California in USA is used to illustrate the proposed framework and demonstrate the computational efficiency of MARS-based Bayesian inversion. The developed MARS models are also used to efficiently drive calculation of Sobol’ total sensitivity indices. Furthermore, only top sensitive parameters are included in Bayesian inference to further improve the computational efficiency of inversion. Sensitivity analysis also confirms that water circulation through high permeable structures, rather than heat conduction through impermeable granite, is the primary heat transfer method. The presented framework is demonstrated an efficient tool to update knowledge of geothermal prospects by inversing field data. Although only thermal data is used in this study, other type of data, such as flow and transport observations, can be jointly used in this method for underground hydrocarbon reservoirs.

15 GEOTHERMAL ENERGY↗

DOE OSTI2015

SU-F-BRD-13: A Phenomenological Relative Biological Effectiveness (RBE) Model for Proton Therapy Based On All Published in Vitro Cell Survival Data

Purpose: Proton therapy treatments are currently planned and delivered using the assumption that the proton relative biological effectiveness (RBE) relative to photons is 1.1. This assumption ignores strong experimental evidence that suggests the RBE varies. A recent review study (Paganetti 2014), collected over 72 experimental reports on proton RBE, providing a comprehensive dataset for predicting proton RBE. Using this dataset we develop a model to predict RBE based on dose, linear energy transfer (LET) and the tissue specific parameter (α/β)x. Methods: The relationship of the RBE on dose, dose average LET (LETd) and (α/β)x was explored using 290 experimental data points. The RBE was calculated for each experimental point for doses ranging from 1 to 10 Gy. An RBE model, based on the linear-quadratic model, was derived using a nonlinear regression fit to the experimental data. Results: The proposed RBE model predicts that the RBE increases with LET and decreases with (α/β)x. The model additionally predicts a decrease in RBE with increasing dose for low (α/β)x values (< 3 Gy). However the model predicts an increase in RBE with increasing dose for large (α/β)x (> 4 Gy). Previous phenomenological models were based on a small subset of experimental data and deviate significantly from our findings. Conclusion: The proposed RBE model is derived using the most comprehensive collection of proton RBE experimental data to date. The model agrees with previous theoretical predictions on the relationship between RBE, LETd and (α/β)x and also makes predictions on the relationship between RBE and dose. The proposed model shows a relationship between α and LETd but no significant relationship between β and LETd. Previously published phenomenological models based on a limited data set might have to be revised.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TU-A-9A-03: Development and Verification of a Forward Model That Assists in Iterative Post-Processing Algorithms Used to Reduce Blur in Compton Backscatter Imaging Systems

Purpose: In Compton Backscatter Imaging (CBI), the source and detector reside on the same side of the patient. We previously demonstrated the applicability of CBI systems for medical purposes using an industrial system. To assist in post-processing images from a CBI system, a forward model based on radiation absorption and scatter principles has been developed. Methods: The forward model was developed in C++ using raytracing to track particles. The algorithm accepts phantoms of any size and resolution to calculate the fraction of incident photons scattered back to the detector, and can perform these calculations for any detector geometry and source specification. To validate the model, results were compared to MCNP-X, which is a Monte Carlo based simulation software, for various combinations of source specifications, detector geometries, and phantom compositions. Results: The model verified that the backscatter signal to the detector was based on three interaction probabilities: a) attenuation of photons going into the phantom, b) Compton scatter of photons toward the detector, and c) attenuation of photons coming out of the phantom. The results from the MCNP-X simulations and the forward model varied from 1 to 5%. This difference was less than 1% for energies higher than 30 keV, but was up to 4% for lower energies. At 50 keV, the difference was less than 1% for multiple detector widths and for both homogeneous and heterogeneous phantoms. Conclusion: As part of the optimization of a medical CBI system, an efficient and accurate forward model was constructed in C++ to estimate the output of CBI system. The model characterized individual components contributing to CBI output and increased computational efficiency over Monte Carlo simulations. It is now used in the development of novel post-processing algorithms that reduce image blur by reversing undesired contribution from outside the region of interest.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2018

Consumption-based greenhouse gas emissions accounting with capital stock change highlights dynamics of fast-developing countries

Traditional consumption-based greenhouse gas emissions accounting attributed the gap between consumption-based and production-based emissions to international trade. Yet few attempts have analyzed the temporal deviation between current emissions and future consumption, which can be explained through changes in capital stock. Here we develop a dynamic model to incorporate capital stock change in consumption-based accounting. The new model is applied using global data for 1995–2009. Our results show that global emissions embodied in consumption determined by the new model are smaller than those obtained from the traditional model. The emissions embodied in global capital stock increased steadily during the period. However, capital plays very different roles in shaping consumption-based emissions for economies with different development characteristics. As a result, the dynamic model yields similar consumption-based emissions estimation for many developed countries comparing with the traditional model, but it highlights the dynamics of fast-developing countries.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Controlling Microbial Byproducts using Model-Based Substrate Monitoring and Control Strategies

We have developed a computer-controlled bioreactor system to study various aspects of microbially-mediated nitrogen cycling. The system has been used to investigate methods for controlling microbial denitrification (the dissimilatory reduction of nitrate to N2O and N2) in hydroponic plant growth chambers. Such chambers are key elements of advanced life support systems being designed for use on long duration space missions, but nitrogen use efficiency in them is reduced by denitrification. Control software architecture was designed which permits the heterogeneous control of system hardware using traditional feedback control, and quantitative and qualitative models of various system features. Model-based feed forward control entails prediction of future systems in states and automated regulation of system parameters to achieve desired and avoid undesirable system states. A bacterial growth rate model based on the classic Monod model of saturation kinetics was used to evaluate the response of several individual denitrifying species to varying environmental conditions. The system and models are now being applied to mixed microbial communities harvested from the root zone of a hydroponic growth chamber. The use of a modified Monod organism interaction model was evaluated as a means of achieving more accurate description of the dynamic behavior of the communities. A minimum variance parameter estimation routine was also' used to calibrate the constant parameters in the model by iterative evaluation of substrate (nitrate) uptake and growth kinetics. This representation of processes and interactions aids in the formulation of control laws. The feed forward control strategy being developed will increase system autonomy, reduce crew intervention and limit the accumulation of undesirable waste products (NOx).

Smernoff, David T.↗

NASA NTRS2015

Development and Characterization of a Rate-Dependent Three-Dimensional Macroscopic Plasticity Model Suitable for Use in Composite Impact Problems

Several key capabilities have been identified by the aerospace community as lacking in the material/models for composite materials currently available within commercial transient dynamic finite element codes such as LS-DYNA. Some of the specific desired features that have been identified include the incorporation of both plasticity and damage within the material model, the capability of using the material model to analyze the response of both three-dimensional solid elements and two dimensional shell elements, and the ability to simulate the response of composites composed with a variety of composite architectures, including laminates, weaves and braids. In addition, a need has been expressed to have a material model that utilizes tabulated experimentally based input to define the evolution of plasticity and damage as opposed to utilizing discrete input parameters (such as modulus and strength) and analytical functions based on curve fitting. To begin to address these needs, an orthotropic macroscopic plasticity based model suitable for implementation within LS-DYNA has been developed. Specifically, the Tsai-Wu composite failure model has been generalized and extended to a strain-hardening based orthotropic plasticity model with a non-associative flow rule. The coefficients in the yield function are determined based on tabulated stress-strain curves in the various normal and shear directions, along with selected off-axis curves. Incorporating rate dependence into the yield function is achieved by using a series of tabluated input curves, each at a different constant strain rate. The non-associative flow-rule is used to compute the evolution of the effective plastic strain. Systematic procedures have been developed to determine the values of the various coefficients in the yield function and the flow rule based on the tabulated input data. An algorithm based on the radial return method has been developed to facilitate the numerical implementation of the material model. The presented paper will present in detail the development of the orthotropic plasticity model and the procedures used to obtain the required material parameters. Methods in which a combination of actual testing and selective numerical testing can be combined to yield the appropriate input data for the model will be described. A specific laminated polymer matrix composite will be examined to demonstrate the application of the model.

Impact↗

NASA NTRS1999

ASTER Digital Elevation Models

This document is based on information and ideas developed by members of the ASTER Digital Elevation Model Working Group (ADEMWG).

ASTER digital elevation model geometric D-13751↗

NASA NTRS2006

Development and Verification of a Finite-Difference Model of the Sorbent-Based Atmosphere Revitalization System for the Crew Exploration

A vacuum-swing adsorption (VSA) process to remove metabolic water, metabolic carbon dioxide, and metabolic and equipment generated trace contaminant gases from the Crew Exploration Vehicle (CEV) atmosphere is being designed. For the CEV, the approach is taken that all metabolic water must be removed by the Sorbent-Based Atmosphere Revitalization System (SBAR), a technology approach that has not been used in previous spacecraft life support systems. To support the design of the SBAR, a Finite Difference computer model has been developed. In addition, examination of the competitive adsorption aspects of water and carbon dioxide on various sorbents is being investigated in order to both refine the computer simulation and gain understanding of the VSA process

Ritter, James↗

NASA NTRSDate not supplied

Multiobjective Multidisciplinary Optimization of Low-Boom Supersonic Transports Using Multifidelity Models

A multidisciplinary optimization (MDO) method has been developed to design a computational fluid dynamics (CFD) based low-boom configuration that can be obtained from a Pareto solution of a low-fidelity multiobjective MDO problem with mission constraints. This paper refines the developed MDO method using multifidelity models for CFD-based multiobjective MDO. The refined MDO method can generate a low-boom configuration that satisfies the mission requirements, has the lowest takeoff gross weight and the longest range for the low-boom mission, trims the low-boom cruise flight with fuel redistributions, and has a reversed equivalent area distribution closely matching a low-boom target with ground noise level below 70 PLdB. The validity of the refined MDO method is demonstrated by a design study of a low-boom supersonic transport that carries 40 passengers, flies a low-boom mission with cruise Mach of 1.7 and range of 3500 nm, and cruises overwater at Mach 1.8 with range of 3882 nm. Moreover, the refined MDO method eliminates the difference between the assumed cruise weight for CFD-based low-boom inverse design optimization and the estimated cruise weight of the optimal inverse design solution with respect to the mission requirements.

multidisciplinary optimization↗

DOE OSTI2015

Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization

Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R{sup 2} = 0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q{sup 2}{sub ext} = 0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential. - Highlights: • It was compiled the largest publicly-available skin permeability dataset. • Predictive QSAR models were developed for skin permeability. • No concordance between skin sensitization and skin permeability has been found. • Structural rules for optimizing sensitization and penetration were established.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Model-based Design Optimization to Achieve the Performance Goals (16.0 SEER/9.5 HSPF), Developing Heat Pump by Using Low-GWP Refrigerants and 5 mm Diameter Tubes

Usage of low-GWP refrigerants can reduce the Green House Gas (GHG) emission of HVAC systems. Our research in previous milestone report has shown that using heat exchangers with 5 mm diameter tubes instead of 9 mm diameter tubes is a promising solution to meet the performance goals of heat pump using low-GWP refrigerants. In addition, the 5mm tube heat exchangers can lead to lower system refrigerant charge and as a result, reduce environmental impact further. However, shifting to small tube diameters requires in-depth heat exchanger design optimization to adapt to the transition to low-GWP refrigerants. In the 2nd quarter of FY21, we conducted multi-objective optimizations using Particle Swarm Optimization algorithm on a residential 5-ton air source heat pump to investigate the potential system performance improvements and material savings. 4 low-GWP refrigerants, ARM20A, ARM20B, R454A and R454C are investigated in this study. The objectives of the optimization are to minimize the heat pump material cost and to maximize the system performance simultaneously. As a result, the HXs material cost is reduced by up to 77% according to the copper and aluminum material price in current market. Under heating mode operation, the smart 4-way valve guarantees that the optimal low-GWP systems maintain or outperform the heating performance of the R410A baseline system. The model-based design optimization yields 18.3-18.9 SEER and 10.6-11.9 HSPF for optimal systems using different low-GWP refrigerants. The initial performance goals (16.0 SEER/9.5 HSPF) are achieved. Furthermore, up to 50% system refrigerant charge reduction is possible in the optimized low-GWP heat pump system using ARM20B. And 91%-95% predicted life-time direct CO 2 emission reduction is achieved by using the optimal 5mm tube low-GWP heat pumps. The significant material saving, charge reduction and direct CO 2 emission reduction help in reducing the environmental impacts of heat pump systems. The optimal heat exchangers resulting from this research can fit into the original baseline indoor and outdoor fan-coil unit. This can reduce the retrofitting effort by minimizing the change in manufacturing and installation of the heat pumps and guarantee the compatibility with end-users’ house structure. Finally, the new products can be easily accepted by manufacturers and end-users.

42 ENGINEERING↗

NASA NTRS2017

CIMI Simulations with Newly Developed Multiparameter Chorus and Plasmaspheric Hiss Wave Models

Numerical simulation studies of the Earth's radiation belts are important to understand the acceleration and loss of energetic electrons. The Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model considers the effects of the ring current and plasmasphere on the radiation belts to obtain plausible results. The CIMI model incorporates pitch angle, energy, and cross diffusion of electrons, due to chorus and plasmaspheric hiss waves. These parameters are calculated using statistical wave distribution models of chorus and plasmaspheric hiss amplitudes. However, currently, these wave distribution models are based only on a single-parameter, geomagnetic index (AE) and could potentially underestimate the wave amplitudes. Here we incorporate recently developed multiparameter chorus and plasmaspheric hiss wave models based on geomagnetic index and solar wind parameters. We then perform CIMI simulations for two geomagnetic storms and compare the flux enhancement of megavolt electrons with data from the Van Allen Probes and Akebono satellites. We show that the relativistic electron fluxes calculated with multiparameter wave models resemble the observations more accurately than the relativistic electron fluxes calculated with single-parameter wave models. This indicates that wave models based on a combination of geomagnetic index and solar wind parameters are more effective as inputs to radiation belt models.

Aryan, Homayon↗

NASA NTRS2000

Investigations of Clouds and Aerosols on Mars, Venus and Titan

For Titan our interest during the past few years was to explain the observed asymmetry in the albedo. We suggested earlier, from one-dimensional modeling studies, that vertical transport rates were comparable to particle fall speeds. Since heating of the upper atmosphere, which drives dynamical motions, is largely due to the aerosols, a non- linear interaction between dynamics, radiative heating and particle microphysics is possible. We pursued this interaction in a two-dimensional model. We showed that the observed variations in the albedo between the two hemispheres and over an orbital cycle, could be due to dynamical motions suspending particles so that particle sizes and optical depths vary across the planet. In the Cassini time frame, future studies of this interaction between dynamics, radiation and microphysics may be worthwhile using the strong modeling base that others, and we have developed. In our recently approved proposal, however, we plan to extend our modeling to hydrocarbon clouds that lie at lower levels. We know very little about such clouds, and numerical models for their properties are non-existent. These clouds may be observed by the Huygen's Probe, and by the Cassini orbiter, so predictions of their properties should help in the analysis of Cassini data. We have also developed a sophisticated model for the lower, condensational, clouds on Venus. In this model we explored the water vapor budget on Venus, and the properties of the clouds such as particle size distribution. Most researchers have investigated the upper clouds on Venus, which are essentially a photochemical aerosol with a long lifetime. The lower clouds, however, are similar to stratus clouds on Earth. These clouds have short lifetimes, and are tightly coupled to the dynamics at the base of the Venus cloud deck. We believe that the holes in these clouds seen at near infrared wavelengths by Galileo are related to some interaction between dynamics and cloud physics. One goal of our recently approved proposed work is to better understand this interaction, and to better understand how these clouds may vary if the climate of Venus were to vary. During the past few years we have applied our model of the water ice clouds on Mars to new data sets from Pathfinder, and Mars Global Surveyor. We have compared our predictions of cloud properties with those seen by Pathfinder, and found reasonable agreement. More recently we have improved our model by including a radiative transfer algorithm and a boundary layer transport scheme . The goal of this work is to understand the thermal inversions seen in Mars Global Surveyor data. We find that the inversions are created by clouds radiatively cooling the atmospheric layers in which the clouds form. We have also initiated laboratory work on the physics of carbon dioxide particle formation. In our recently approved work we propose to use these laboratory data, and to extend our modeling to carbon dioxide clouds in the Martian atmosphere.

Toon, Owen B.↗

DOE OSTI2023

Machine learning based simultaneous control of air handling unit discharge air and condenser water temperatures set-point for minimized cooling energy in an office building

In this study, an artificial intelligence based real-time prediction and control model to optimize condenser water temperature and discharge air temperature (DAT) set-points in water-cooled air handling unit (AHU) system has been developed. EnergyPlus-MATLAB co-simulation has been conducted to analyze the developed model's effectiveness. Here, to develop artificial neural networks (ANN) model, embedded neural network objects in MATLAB was utilized. The developed model could decide an optimal temperature set-points based on outdoor air wet-bulb temperature to reflect the Korean climate context. As a result, the developed ANN prediction model showed the predictive performance of Cv(RMSE) of approximately 21%. Compared to the conventional fixed temperature algorithm, which fixes AHU DAT at 14°C and condenser water temperature at 32°C, the ANN based optimized control showed a 22% total cooling energy reduction. These results show that significant energy savings can be achieved by simultaneously controlling condenser water temperature and AHU DAT set-points considering Korean climatic characteristics using AI technologies such as ANN models.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1991

Fourier functional analysis for unsteady aerodynamic modeling

A method based on Fourier analysis is developed to analyze the force and moment data obtained in large amplitude forced oscillation tests at high angles of attack. The aerodynamic models for normal force, lift, drag, and pitching moment coefficients are built up from a set of aerodynamic responses to harmonic motions at different frequencies. Based on the aerodynamic models of harmonic data, the indicial responses are formed. The final expressions for the models involve time integrals of the indicial type advocated by Tobak and Schiff. Results from linear two- and three-dimensional unsteady aerodynamic theories as well as test data for a 70-degree delta wing are used to verify the models. It is shown that the present modeling method is accurate in producing the aerodynamic responses to harmonic motions and the ramp type motions. The model also produces correct trend for a 70-degree delta wing in harmonic motion with different mean angles-of-attack. However, the current model cannot be used to extrapolate data to higher angles-of-attack than that of the harmonic motions which form the aerodynamic model. For linear ramp motions, a special method is used to calculate the corresponding frequency and phase angle at a given time. The calculated results from modeling show a higher lift peak for linear ramp motion than for harmonic ramp motion. The current model also shows reasonably good results for the lift responses at different angles of attack.

Lan, C. Edward↗

NASA NTRS1991

Fourier functional analysis for unsteady aerodynamic modeling

Chin, Suei↗

DOE OSTI2023

First Principles Modeling of Cluster-Based Solid Electrolytes (Final Technical Report)

Given the trend of global warming and the urgent need to transition from fossil fuels to green energy, lithium-ion batteries continue to be an integral part of our lives. Design, development, and understanding of novel solid-state electrolyte materials play the key role for achieving next-generation all-solid-state batteries with high energy and great safety. The current modeling schemes to develop advanced solid electrolytes are focusing on materials in which the building blocks are individual atoms. Our theoretical approach is a paradigm shift in solid-state electrolyte design. Instead of atoms, we focus on clusters as the building blocks and model these solid electrolytes and their interfaces with electrodes, especially Li-metal anode, for their successful implementation in solid-state batteries. The advantage of using the cluster ions to replace elemental ions is that the size, composition, and shape of the former can be tailored to achieve higher ionic conductivity at room temperature, electrochemical stability, and charge transfer across solid-solid interfaces than conventional materials. Specifically, the project includes: (1) Developing cluster-based solid electrolytes, where the halogen components are replaced by cluster ions that mimic the chemistry of halogens but are characterized by additional degrees of freedom, including the size, shape, composition, and motional dynamics under excitation. (2) Providing a fundamental understanding of the ion conduction mechanism in the developed cluster-based solid electrolytes; (3) Modeling the interfacial properties (i.e., structural, chemical, and transport properties) between the cluster-based solid electrolytes and electrodes at the atomic level. For the cluster-based solid electrolytes incompatible with the Li-metal anode or cathode materials, potential candidates for interfacial coatings are identified and studied. (4) Providing a theoretical framework towards optimizing critical parameters of the solid-state electrolytes that guides experimentalists to attain desired cathode-electrode interface for cluster-based solid-state electrolytes.

25 ENERGY STORAGE↗

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