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At least 865 records · Page 48

All sources NASA NTRS DOE OSTI

DOE OSTI2018

Validation and optimization of batch and continuous particle separation processes

Recent advances in simulation capabilities coupled with advanced manufacturing can be leveraged to create highly efficient compact reactors with low emissions, low cost, high reliability, and high flexibility for energy conversion. This type of reactor is especially important for conversion of bio-mass, a storable, renewable and fast-growing energy source, considering the distributed nature of raw material and cost of biomass collection and transportation. To achieve this goal, it is critical to developing new process technologies that are significantly more efficient than traditional processes for which the added manufacture provides a fast way of realization and evaluation. Based upon the flagship MFiX multiphase computational fluid dynamic software suite, NETL has developed an Optimization Toolset to facilitate the CFD simulation based reactor design and optimization, and process intensification. This technical report presents the recent development and application of the Optimization Toolset and the framework for process optimization of particle separation in batch and continuous processes. In these processes, a fluidized bed reactor under proper operating condition was used to separate particles of different physical properties. MFiX-DEM simulations were conducted for a batch system to simulate the process covering a wide range of superficial gas velocities from which the optimal operational parameter can be determined through analyzing the system response. After successful demonstration of the framework, a continuous system for particle separation was designed based on CFD simulations. Similar optimization exercises were conducted for the continuous particle separation considering multiple operating parameters. The design was then fabricated in the laboratory through 3D printing for testing. The particle separation performance was carefully measured through high-speed video for particle tracking. Quantitative comparison between numerical results and experimental measurements were conducted for confirmation and validation.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2019

Decomposition of plasma kinetic entropy into position and velocity space and the use of kinetic entropy in particle-in-cell simulations

In this work, we describe a systematic development of kinetic entropy as a diagnostic in fully kinetic particle-in-cell (PIC) simulations and use it to interpret plasma physics processes in heliospheric, planetary, and astrophysical systems. In the beginning, we calculate kinetic entropy in two forms—the “combinatorial” form related to the logarithm of the number of microstates per macrostate and the “continuous” form related to flnf, where f is the particle distribution function. We discuss the advantages and disadvantages of each and discuss subtleties about implementing them in PIC codes. Using collisionless PIC simulations that are two-dimensional in position space and three-dimensional in velocity space, we verify the implementation of the kinetic entropy diagnostics and discuss how to optimize numerical parameters to ensure accurate results. We show the total kinetic entropy is conserved to three percent in an optimized simulation of antiparallel magnetic reconnection. Kinetic entropy can be decomposed into a sum of a position space entropy and a velocity space entropy, and we use this to investigate the nature of kinetic entropy transport during collisionless reconnection. We find the velocity space entropy of both electrons and ions increases in time due to plasma heating during magnetic reconnection, as the position space entropy decreases due to plasma compression. This project uses collisionless simulations, so it cannot address physical dissipation mechanisms; nonetheless, the infrastructure developed here should be useful for studies of collisional or weakly collisional heliospheric, planetary, and astrophysical systems. Beyond reconnection, the diagnostic is expected to be applicable to plasma turbulence and collisionless shocks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1972

Analysis and design of three dimensional supersonic nozzles. Volume 3: A design technique for multiple nozzle configurations

An iteration procedure for optimum nozzle design with application to hypersonic aircraft is discussed. In the procedure, intial values of several of the design parameters are assumed from simplified approximate considerations and are then varied systematically in order to determine the value of each parameter which optimizes nozzle performance. Improvements in nozzle performance are obtained by perturbing the initially assumed values of the geometric parameters on the basis of a computer analysis.

Ferri, A.↗

NASA NTRS1988

Application of fuzzy theories to formulation of multi-objective design problems

Much of the decision making in real world takes place in an environment in which the goals, the constraints, and the consequences of possible actions are not known precisely. In order to deal with imprecision quantitatively, the tools of fuzzy set theory can by used. This paper demonstrates the effectiveness of fuzzy theories in the formulation and solution of two types of helicopter design problems involving multiple objectives. The first problem deals with the determination of optimal flight parameters to accomplish a specified mission in the presence of three competing objectives. The second problem addresses the optimal design of the main rotor of a helicopter involving eight objective functions. A method of solving these multi-objective problems using nonlinear programming techniques is presented. Results obtained using fuzzy formulation are compared with those obtained using crisp optimization techniques. The outlined procedures are expected to be useful in situations where doubt arises about the exactness of permissible values, degree of credibility, and correctness of statements and judgements.

Dhingra, A. K.↗

DOE OSTI2024

MxRAM (Final Report)

Sandia National Labs will provide Technical Assistance and consulting to Requester on a series of Requester’s test structures and devices to characterize and aid in the determination of optimal fabrication parameters via fabrication of functional test structures and cells. Working with previously established processes and test die modules, Sandia will construct a series of test chips with varying materials properties to allow the electrical characterization and component testing of Requester’s test structures and devices. Material variations will be selected for optimization of yield and desired target operation parameters. A deliverable in the form of a report will be written. Sandia intends to deliver testable die to the Requester.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Scalable Preconditioning of Block-Structured Linear Algebra Systems using ADMM

In this paper, we study the solution of block-structured linear algebra systems arising in optimization by using iterative solution techniques. These systems are the core computational bottleneck of many problems of interest such as parameter estimation, optimal control, network optimization, and stochastic programming. Our approach uses a Krylov solver (GMRES) that is preconditioned with an alternating method of multipliers (ADMM). We show that this ADMM-GMRES approach overcomes well-known scalability issues of Schur complement decomposition in problems that exhibit a high degree of coupling. The effectiveness of the approach is demonstrated using linear systems that arise in stochastic optimal power flow problems and that contain up to 2 million total variables and 4,000 coupling variables. We find that ADMM-GMRES is nearly an order of magnitude faster than Schur complement decomposition. Moreover, we demonstrate that the approach is robust to the selection of the augmented Lagrangian penalty parameter, which is a key advantage over the direct use of ADMM.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Sparse regression for plasma physics

Many scientific problems can be formulated as sparse regression, i.e., regression onto a set of parameters when there is a desire or expectation that some of the parameters are exactly zero or do not substantially contribute. This includes many problems in signal and image processing, system identification, optimization, and parameter estimation methods such as Gaussian process regression. Sparsity facilitates exploring high-dimensional spaces while finding parsimonious and interpretable solutions. In the present work, we illustrate some of the important ways in which sparse regression appears in plasma physics and point out recent contributions and remaining challenges to solving these problems in this field. Further, a brief review is provided for the optimization problem and the state-of-the-art solvers, especially for constrained and high-dimensional sparse regression.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2004

Optimal Sensor Allocation for Fault Detection and Isolation

Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

Azam, Mohammad↗

DOE OSTI2022

Building energy efficiency and load flexibility optimization using phase change materials under futuristic grid scenario

This work investigates the energy savings and load flexibility capacity of phase change material (PCM) integrated into building envelope under a future energy generation scenario, where 80% of the energy load comes from renewable sources. Using community-scale modeling, we first determine the net thermal storage required to fully manage the demand variability at a utility grid, and then using whole-building simulations we optimize operating parameters - such as PCM thickness, latent heat, interior setpoint profile, PCM distribution, and heat transfer coefficient - to determine the optimal conditions required for maximum energy reduction and load flexibility without compromising occupants' thermal comfort. The optimal PCM-integrated envelope proposed in this study can provide annual load flexibility up to 33.6% and annual energy savings up to 10.8% in a lightweight residential building located in Baltimore, MD. This study is relevant given the increasing contributions of renewable energy in the total energy generation mix, leading to a significant time-imbalance between peak energy demand and peak energy production. While thermal energy storage using PCM is a recognized technique, there is no known prior study dedicated to examining the thermal performance of PCM-integrated envelope under future energy generation scenarios. This study bridges the research gap by investigating a practical way to implement PCMs in the buildings and maximize the energy efficiency as well as load flexibility related benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Retrieval of high time resolution growth factor probability density function from a humidity-controlled fast integrated mobility spectrometer

Hygroscopicity describes the tendency of aerosol particle to uptake water and is among the key parameters in determining the impact of atmospheric aerosols on global radiation and climate. A hygroscopicity tandem differential mobility analyzer (HTDMA) system is the most widely utilized instrument for determining the aerosol hygroscopic growth. Because of the time needed to scan the classifying voltage of the DMA, HTDMA measurement normally requires a minimum of 30 min to characterize the particle hygroscopic growth at a single relative humidity for five to six different sizes. This slow speed is often inadequate for measurements onboard mobile platforms or when aerosols evolve rapidly. Recently, a humidity-controlled fast integrated mobility spectrometer (HFIMS) was developed for measuring the hygroscopic growth of particles. The measurement speed of the HFIMS is about one order of magnitude faster than that of the conventional HTDMA. Here, a data inversion routine is developed to retrieve the growth factor probability density function (GF-PDF) of particles measured by the HFIMS. The inversion routine considers the transfer functions of the upstream DMA and the downstream water-based fast integrated mobility spectrometer (FIMS), and derives the GF-PDF that reproduces the measured responses of the HFIMS. The performance of the inversion routine is examined using ambient measurements with different assumptions for the spectral shape of the particle GF-PDF (multimodal lognormal or piecewise linear). The influences of the data inversion parameters and counting statistics on the inverted GF-PDFs were further investigated, and an approach to determine the optimized inversion parameters is presented.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Simulating scalar field theories on quantum computers with limited resources

Here we present a quantum algorithm for implementing φ 4 lattice scalar field theory on qubit computers. The field is represented in the discretized field amplitude basis. The number of qubits and elementary gates required by the implementation of the evolution operator is proportional to the lattice size. The algorithm allows efficient φ 4 state preparation for a large range of input parameters in both the normal and broken-symmetry phases. The states are prepared using a combination of variational and adiabatic evolution methods. First, the ground state of a local Hamiltonian, which includes the φ 4 self-interaction, is prepared using short variational circuits. Next, this state is evolved by switching on the coupling between the lattice sites adiabatically. The parameters defining the local Hamiltonian are adjustable and constitute the input of our algorithm. We present a method to optimize these parameters in order to reduce the adiabatic time required for state preparation. For preparing broken-symmetry states, the adiabatic evolution problems caused by crossing the phase transition critical line and by the degeneracy of the broken-symmetry ground state can be addressed using an auxiliary external field which gradually turns off during the adiabatic process. We show that the time dependence of the external field during the adiabatic evolution is important for addressing the broken-symmetry ground state degeneracy. The adiabatic time dependence on the inverse error tolerance can be reduced from quadratic to linear by using a field strength that decreases exponentially in time relative to one that decreases linearly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1990

Influence of structural and aerodynamic modeling on optimization with flutter constraint

The influences of structural and aerodynamic modeling on multidisciplinary optimization in an aeroelastic environment are not well understood. Therefore, optimizations with flutter and frequency constraints were performed to investigate the effects these modeling factors have on various representative wings. To this end, the Automated Structural Optimization System (ASTROS) was used as a tool to minimize the weight of various fully built-up finite element wing models in subsonic and supersonic flow under given flutter and frequency constraints. First, the performance of the optimization module was tested against results from other codes on a straight and uniform wing widely used for optimization with flutter constraints. Then, fully built-up finite element models of various wings with different aspect ratios were investigated for the influence on the structural optimization for minimum weight of the following modeling factors: finite element selection, structural grid refinement; number of selected modes, retention of breathing modes; selection of reduced frequencies to be used in flutter analysis; aerodynamic panel size and placement; splining of the aerodynamic grid to the structural grid selection of extra points of the structural wing box for splining; and number of constraints to be retained. Knowledge of these influences as well as of the program behavior is important, since optimization can be made more efficient by the selection of reasonable initial models. Also, it was shown previously that modeling has an impact on the results of modal and aeroelastic analyses. Thus, if modeling errors can negatively affect the analyses, a minimum weight optimization can be jeopardized and result in an optimal design that is rather unreliable. In the following, selected results are presented and the influences of some modeling parameters on optimization are pointed out.

Striz, Alfred G.↗

NASA NTRS2019

Mitigation Strategies for Space Radiation Health Risks

Astronauts embarking on missions beyond low Earth orbit (LEO) will be exposed to a radiation field that may increase the risks of developing cancer, cardiovascular diseases, central nervous system disorders, and immune decrements. Operational parameters will be the primary determinants of crew radiation exposure. NASA uses integrated design tools and risk models to optimize these parameters to minimize radiation exposure. NASA is also considering medical countermeasures (MCMs) to reduce radiation-associated health risks. MCMs for potential use in space-based applications can be developed from a variety of sources, including: a) population-based chemoprevention trials against targeted diseases b) drug development efforts focused on treating acute effects from accidental radiation exposures c) drug development to mitigate side effects of radiotherapy d) mechanistic studies of distinct damage caused by high charge (Z) and energy (HZE) radiation. Use of agents developed for other applications, or repurposed, is advantageous because long-term safety in humans is already established.

Huff, Janice L.↗

NASA NTRS2019

On-Orbit Xenon Refueling Loading Times and Transient Analysis

The Power and Propulsion Element (PPE) of the Lunar Orbital Platform-Gateway will demonstrate the first on-orbit refueling of xenon propellant for a solar electric propulsion system. An analysis was performed in Microsoft Excel to determine what factors influence the overall refueling time of a single 2,000-kilogram capacity xenon propellant tank, as well as provide estimates for overall refueling duration. Due to the high heat of compression of xenon, the propellant tank could exceed its maximum allowable temperature during refueling if the xenon flow rate and temperature are unregulated. In order to prevent overheating, a logic based "bang-bang" operation was used for refueling, shutting off the mass feed when the tank reached a maximum temperature. Heat is removed from the tank via radiation to the surrounding spacecraft bus. The analysis shows that optimizing key parameters such as mass flow rate into the tank, residual propellant in the tank during the onset of refueling, and tank diameter significantly reduces the overall refueling duration. Optimization is not straightforward, however, as the loading time does not trend monotonically with the parameters. Overall, the most significant impact on loading duration comes from altering the residual propellant in the tank. Increasing the mass of residual propellant from 2 percent to 20 percent reduces the overall refueling duration by 56 percent. Future work based on this analysis includes creation of a SINDA/FLUINT model and building a ground-based xenon refueling system emulator.

Xenon↗

DOE OSTI2023

Designing an Optimal LSST Deep Drilling Program for Cosmology with Type Ia Supernovae

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) is forecast to collect a large sample of Type Ia supernovae (SNe Ia) expected to be instrumental in unveiling the nature of dark energy. The feat, however, requires accurately measuring the two components of the Hubble diagram, distance modulus and redshift. Distance is estimated from SN Ia parameters extracted from light-curve fits, where the average quality of light curves is primarily driven by survey parameters. An optimal observing strategy is thus critical for measuring cosmological parameters with high accuracy. We present in this paper a three-stage analysis to assess the impact of the deep drilling (DD) strategy parameters on three critical aspects of the survey: redshift completeness, the number of well-measured SNe Ia, and cosmological measurements. We demonstrate that the current DD survey plans (internal LSST simulations) are characterized by a low completeness (z ~ 0.55–0.65), and irregular and low cadences (several days), which dramatically decrease the size of the well-measured SN Ia sample. We propose a method providing the number of visits required to reach higher redshifts. We use the results to design a set of optimized DD surveys for SN Ia cosmology taking full advantage of spectroscopic resources for host galaxy redshift measurements. The most accurate cosmological measurements are achieved with deep rolling surveys characterized by a high cadence (1 day), a rolling strategy (at least two seasons of observation per field), and ultradeep (z ≳ 0.8) and deep (z ≳ 0.6) fields. A deterministic scheduler including a gap recovery mechanism is critical to achieving a high-quality DD survey.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Microfluidic Uranium Microspheres Production for TRISO and Advanced Fuel Concepts

The purpose of this project was to expand existing internal gelation sol-gel capabilities at PNNL to explore producing uranium dioxide spheres for potential use as fuel kernels in next generation Tri-isotropic (TRISO) particle fuel. This project expands on previous sol-gel efforts at PNNL by (1) increasing the size regime of sphere production from the micro-fluidic range to the milli-fluidic range, and (2) producing uranium spheres. The approach involved first scaling up the channel size of the fluidic system to the millimeter range, with radiation safety considerations in mind; testing and demonstration on non-radioactive surrogate material, cerium oxide; then transitioning to uranium production and finally optimizing system parameters. Commercially available fluidic chips in the desired size range were could not be found, therefore the project designed and fabricated a T-junction with 1mm channels for droplet production. Because the production process is temperature sensitive, prior efforts have involved performing droplet production in a lab freezer. To reduce radiological waste and footprint, two alternative chilling methods were explored using aluminum thermal beads as a chill bath and a custom aluminum block fit to reagent reservoir sizes. Both were successful in the cerium tests, however the aluminum block design outperformed the thermal bead bath and was further adapted for the radiological test and production run in the Radiochemical Processing Laboratory (RPL). Gelation trials were performed to determine an acceptable range of feed solution parameters for the uranium dioxide gels, characterized by R-values, which is determined by the ratio of uranium nitrate to Hexamethylenetetramine (HMTA)/urea in the feed solution. R-values ranging from 1.6-2 were examined in the gelation trials, with only the 1.8 condition being tested in production. The project was successful in demonstrating a proof of concept design for producing uranium dioxide spheres, however further optimization is needed to dial in production parameters and improve sphere quality and homogeneity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Clear-sky detection for PV degradation analysis using multiple regression

A method is presented to detect clear-sky periods for plane-of-array irradiance time-averaged data that is based on the algorithm originally described by Reno and Hansen. Here we show this new method improves the state-of-the-art by providing accurate detection at longer data averaging intervals. Moreover, our new method detects clear periods in plane-of-array data, which is novel. The new method is developed by applying a Design of Experiment approach to optimize the parameters used in the Reno method, and Monte Carlo simulations are used to understand the robustness of the found parameters. Clear-sky detection accuracy is compared among four methods: the Reno method, the default clear-sky filter in RdTools, the Ellis method, and the method outlined in this work, using a hand-labeled two-year data set of 1-min plane-of-array irradiance for a fixed tilt system. The RdTools clear-sky filter is marred by excessive false positives. The other methods all perform well at 1-min data intervals; the method developed here provides more accurate detection at longer data averaging intervals. We show that the parameters are directly linked to the data frequency in the hope that these input variables may not have to be optimized for every data frequency and location. However, only a single fixed system in one location was carefully examined. Finally, we illustrate how accurate determination of clear-sky conditions helps to eliminate data noise and bias in the assessment of long-term performance of PV plants.

14 SOLAR ENERGY↗

DOE OSTI2022

Nonunique fraction of Fock exchange for defects in two-dimensional materials

By investigating the vacancy and substitutional defects in monolayer WS 2 with hybrid functionals, we find that there is no unique amount of Fock exchange that concurrently satisfies the generalized Koopmans' condition and reproduces the band-gap and band-edge positions. Fixing the mixing parameter of Fock exchange based on the band gap can lead to qualitatively incorrect defect physics in two-dimensional materials. Instead, excellent agreement is achieved with both experiment and many-body perturbation theory within the GW approximation once the mixing parameters are tuned individually for the defect species and the band edges. Here, we show the departure from a unique optimized mixing parameter is inherent to two-dimensional systems as the band edges experience a reduced screening while the localized defects are subject to bulklike screening.

2-dimensional systems↗