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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimizing Desalination Operations for Energy Flexibility

Despite the value of energy optimization in desalination processes, modeling dynamic operations for monthly billing periods has remained a computational challenge. This work proposes a framework for energy flexibility optimization, which includes new modeling features for independent operation of parallel skids, start-up delays associated with chemical stabilization, the consideration of industrial energy tariff structures, and inclusion of hourly electrical carbon intensities. This is done using a modular and computationally efficient formulation that guarantees a globally optimal solution with standard optimization solvers. In this study, the approach is demonstrated in two distinct case studies: a seawater desalination plant in Santa Barbara, CA, and an indirect potable reuse facility in San Jose, CA. Trends predicted from the model are validated against operational facility measurements from a demand response shutdown event. Preliminary results show that optimizing energy flexibility can result in 18.51% monthly cost savings over energy efficiency-optimized operation. The value extracted from a facility-wide shutdown during peak electricity price hours is hampered by start-up delays in post-treatment chemical stabilization. In cases in which a facility does not have much excess capacity, using a flow equalization tank or operating over a wide recovery range may be cost-effective.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Phase transformation and growth mechanism of RF sputtered ferroelectric lead scandium tantalate (PbSc 0.5 Ta 0.5 O 3 ) films

Lead scandium tantalate (PbSc 0.5 Ta 0.5 O 3 , PST), an order/disorder ferroelectric, is a potential candidate for electrocaloric cooling and pyroelectric infrared (IR) detector. In this work, we report the phase transformation kinetics from two series of samples containing pure amorphous and mixture of amorphous and pyrochlore to desired perovskite phase using postdeposition rapid thermal processing (RTP) as well as growth mechanism of RF sputtered PST thin films using excess lead target on platinized silicon (Pt/Ti/SiO 2 /Si) substrates. We find that small changes in the temperature ramp have a large effect on the degree of perovskite conversion (ferroelectric phase), orientation (crystallographic texture), and long-range order parameter (< S 111 >). Through isothermal annealing, we obtained optimal perovskite phase at ≥700°C temperature. The phase transformation is characterized by spontaneous formation of center-type in-plane radial rosette-like structures revealed by scanning electron microscopy. The PST perovskite crystallites were found to coexist with pyrochlore in RTP annealed films. The volume fractions for perovskite and pyrochlore phase were obtained from the analysis of “rosettes” and respective X-ray diffraction intensities which helped to determine various parameters associated with phase kinetics (n, k, and activation energy, Ea) and accompanying growth. The effective activation energies of perovskite transition and growth were found to be 332 ± 11 kJ/mol (345 ± 11 kJ/mol) and 114 ± 10 kJ/mol (122 ± 10 kJ/mol), respectively, for pure amorphous only (and mixed amorphous and pyrochlore) phase following nucleation-growth controlled Avrami's equation. A linear growth rate (n~1) for the perovskite phase indicates predominant interface-controlled process and diffusion-limited phenomena thus inhibiting rosette size owing to reactant depletion and soft impingement at the grain boundary. However, the growth behavior is isotropic in two-dimension parallel to the plane of the substrates for both sample series. Furthermore, lead loss was severe for in-situ growth and RTP combined with conventional furnace annealing than those of RTP only films, which were closer to stoichiometric albeit with excess lead and marginal oxygen vacancies (V o ).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Vadose Zone Model for A Trenches Area for Composite Analysis

The objectives of the vadose modeling for the updated Hanford Site composite analysis (CA) are to simulate the flow and transport of water and radionuclide releases from the surface to the water table and to provide radionuclide transfer rates for the plateau to river (P2R) model, version 8.3. Water additions include natural recharge and water discharged to the ground as a result of industrial processes associated with Hanford Site operations. Contaminant sources include radionuclides in water discharged to the ground during operations and radionuclides disposed “dry” in solid waste burial grounds or other means. The parallel version of the Subsurface Transport Over Multiple Phases (STOMP) simulator, officially named the exascale Subsurface Transport Over Multiple Phases (eSTOMP), is used to simulate flow and transport for the vadose models. The scope of this ECF is to document the development and results of the A Trenches Area vadose zone model. The A Trenches Area model covers the region between the 200 East Area and southwest of the 216-B-3 Pond. The primary waste sites in this area are cribs associated with PUREX Plant (202-A).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Thermodynamic Limits of Redox-Based Thermochemical Processes (REDOTHERM)

Solar thermochemical fuel production is a potential pathway for the production of sustain liquid drop-in fuels, which can help decarbonize the aviation and maritime sectors. In an attempt to analyze the commercial viability of this technology, several studies have been conducted, including system and technoeconomic analysis (TEA) modeling. However, most studies to date simply assume a given redox reactor efficiency, which is significantly higher than demonstrated values to date. While it is widely recognized that utilizing a counter-current flow (CF) configuration could increase the redox reactor efficiency, an over-simplification in the thermodynamic modeling may lead to unphysical results which has been included in multiple publications. The fact that the solar redox reactor is the least developed component in the process chain makes it hard to identify technology gaps and evaluate pathways to deployment at scale using this approach. In this work, a thermodynamic model for a moving oxide system has been developed, in a general form that allows to analyze the system for different redox-active materials, under a wide range of operating conditions, for both parallel and countercurrent flows. The model capabilites are demonstrated, and the model's code will be shared as an open-source on GitHub in the next few months.

chemical looping↗
DOE OSTI2020

Automated calculation and convergence of defect transport tensors

Defect diffusion is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end-user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewide sampling completeness, to build atomistic kinetic Monte Carlo models on a state-space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for drift and diffusion coefficients, providing a convergence metric by calculating the Kullback–Leibler divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and Hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Implanted Guard Ring Edge Termination With Avalanche Capability for Vertical GaN Devices

Edge termination is the key building block in power devices to enable near-ideal, avalanche breakdown voltage (BV). Here, this work presents the design, fabrication, and physics of a GaN guard ring (GR) edge termination formed by selective-area nitrogen implantation through an epitaxial p-GaN layer. The fabrication of this termination only includes a single implantation step that does not require precise control of implant depth, rendering a large process latitude. The selective-area implantation produces p-GaN rings that are separated by the implanted, semi-insulating regions. The number and spacing of the p-type rings are found to determine the BV of the vertical GaN p-n diode. The 16-ring structure enables a BV of 1800 V, being 88% of the theoretical 1-D parallel-plane limit. Avalanche characteristics are observed in devices with a large variety of GR designs. Finally, we present a comprehensive survey on the efficiency, fabrication complexity, real estate, and avalanche capability of various edge termination techniques that have been reported in vertical GaN devices. The high efficiency (among the highest reported in avalanche-capable GaN terminations), simple and robust fabrication process, and uniform avalanche capability make this implanted GR a promising edge termination for high-voltage GaN devices.

42 ENGINEERING↗
DOE OSTI2026

Low power on-chip data transmission for wafer-scale monolithic active pixel sensors

Here, this paper details the implementation of the digital pulse shaping subsystem within the Backbone Transmission Line Encoding (BTLE) driver, a low-power, long-distance on-chip data transmission solution designed in a 65 nm CMOS process. Digital pulse shaping is critical for minimizing inter-symbol interference (ISI) caused by bandwidth limitations of on-chip interconnects, especially in wafer-scale monolithic active pixel sensors (MAPS). A duobinary encoder coupled with a parallelized polyphase finite impulse response (FIR) filter is used for efficient shaping of the transmitted signal spectrum. This reconfigurable architecture achieves reliable 160 Mb/s data transfer over a 10 cm on-chip link, as validated by simulations demonstrating low power consumption (FoM 37.3 fJ/bit/mm of transmission line length) and effective ISI mitigation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

The Shortwave Spectral Radiometer for Atmospheric Science: Capabilities and Applications from the ARM User Facility

Industry advances have greatly reduced the cost and size of ground-based shortwave (SW) sensors for the ultraviolet, visible, and near-infrared spectral ranges that make up the solar spectrum, while simultaneously increasing their ruggedness, reliability, and calibration accuracy needed for outdoor operation. These sensors and collocated meteorological equipment are an important part of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility, which has supported parallel integrated measurements of atmospheric and surface properties for more than two decades at fixed and mobile sites around the world. The versatile capability of these ground-based measurements includes 1) rich spectral information required for retrieving cloud and aerosol microphysical properties, such as cloud phase, cloud particle size, and aerosol size distributions, and 2) high temporal resolution needed for capturing fast evolution of cloud microphysical properties in response to rapid changes in meteorological conditions. Here we describe examples of how ARM's spectral radiation measurements are being used to improve understanding of the complex processes governing microphysical, optical, and radiative properties of clouds and aerosol.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tensor Extraction of Latent Features (TELF)

Tensor ELF is a user-friendly parallel tensor decomposition Python toolbox that includes a suite of machine learning algorithms for CPU and GPU architectures for the analysis of sparse and dense data including utility tools for pre-processing and post-processing.

Eren, Maksim↗
DOE OSTI2024

Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data

The paper presents the development of algorithms for mass and energy constrained neural network models that can exactly conserve the overall mass and energy of distributed chemical process systems, even though the noisy transient data used for optimal model training violate the same. In contrast to approximately satisfying mass and energy balance constraints of a system by soft penalization of objective function, algorithms have been developed for solving equality-constrained nonlinear optimization problems, thus providing the guarantee of exactly satisfying the system mass and energy conservation laws. For developing dynamic mass-energy constrained network models for distributed systems, hybrid series and parallel dynamic-static neural networks have been leveraged. The developed algorithms for solving both the training and forward problems are validated using both steady-state and dynamic data in the presence of various noise characteristics. The developed data-driven algorithms are flexible to exactly satisfy mass and energy balance constraints for dynamic chemical processes if the system holdup information is available. The proposed network structures and algorithms are applied to the development of data-driven lumped and distributed models of an adiabatic superheater/reheater system, a nonisothermal continuous stirred tank reactor, as well as an electrically heated plug-flow reactor system where one form of energy gets transformed to another. It has been observed that the mass-energy constrained neural networks yield a root mean squared error of <1% with respect to the system truth for the case studies evaluated in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Model-based, in-situ, non-destructive qualification and certification of parts made by autonomous additive manufacturing

To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.

Gunasegaram, Dayalan↗
DOE OSTI2021

3D printing of anisotropic Sm–Fe–N nylon bonded permanent magnets

Abstract Fabricating a bonded magnet with a near‐net shape in suitable thermoplastic polymer binders is of paramount importance in the development of cost‐effective energy technologies. In this work, anisotropic Sm 2 Fe 17 N 3 (Sm–Fe–N) bonded magnets are additively printed using SmFeN anisotropic magnetic particles in a polymeric binder polyamide‐12 (PA12). The anisotropic SmFeN bonded magnets are fabricated by Big Area Additive Manufacturing followed by post‐printing alignment in a magnetic field. Optimal post‐alignment results in an enhanced remanence of ∼0.68 T in PA12 reflected in a parallel‐oriented (aligned) measured direction. The maximum energy product achieved for the additively printed anisotropic bonded magnet of Sm–Fe–N in PA12 polymer is 78.8 KJ m −3 . Our results show advanced processing flexibility with 3D printing of the development of SmFeN nylon bonded magnets designed for applications with no critical rare earth magnets.

42 ENGINEERING↗
DOE OSTI2023

A sensitivity analysis of twinning crystal plasticity finite element model using single crystal and poly crystal Zircaloy

The popularity of crystal plasticity finite element method (CPFEM) models is increasing due to their ability to predict the mechanical response of crystalline materials such as metals and metal alloys more accurately than traditional continuum mechanics models. This is since the crystal plasticity models consider the effect of atomic structure, microstructural morphology, and properties of individual grains. These CPFEM models use a large number of material parameters in order to capture the mesoscale physics which comes with the downside of the tedious calibration process. In this paper, a CPFEM code was developed to include the twinning induced grain reorientation and subsequent crystallographic slip for HPC material. The developed code is incorporated in a large-scale, parallelized nonlinear solver WARP3D. Further, a sensitivity analysis with respect to 22 material parameters was then conducted using single crystal and polycrystal representative volume element (RVE) of Zircaloy material. Loading was applied along five different crystallographic orientations for single crystal RVE and along three directions namely, rolling (RD), transverse (TD), and normal (ND) direction for polycrystal RVE. Results obtained from the sensitivity analysis were used for the calibration of material parameters for Zircaloy. Finally, developed code along with calibrated material parameters was used to investigate the effect of the hydride phase formation in Zircaloy which is a typical case observed for nuclear applications. It was found that the volume fraction of the hydride phase has a significant impact on the mechanical properties of Zircaloy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effects of wave damping and finite perpendicular scale on three-dimensional Alfvén wave parametric decay in low-beta plasmas

Shear Alfvén wave parametric decay instability (PDI) provides a potential path toward significant wave dissipation and plasma heating. However, fundamental questions regarding how PDI is excited in a realistic three-dimensional (3D) open system and how the finite perpendicular wave scale—as found in both laboratory and space plasmas—affects the excitation remain poorly understood. Here, we present the first 3D, open-boundary, hybrid kinetic-fluid simulations of kinetic Alfvén wave PDI in low-beta plasmas. Key findings are that the PDI excitation is strongly limited by the wave damping present, including electron–ion collisional damping (represented by a constant resistivity) and geometrical attenuation associated with the finite-scale Alfvén wave, and ion Landau damping of the child acoustic wave. The perpendicular wave scale alone, however, plays no discernible role: waves of different perpendicular scales exhibit similar instability excitation as long as the magnitude of the parallel ponderomotive force remains unchanged. These findings are corroborated by theoretical analysis and estimates. This new understanding of 3D kinetic Alfvén wave PDI physics is essential for laboratory study of the basic plasma process and may also aid future evaluation of the relevance/role of PDI in low-beta space plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A Cryogenic readout integrated circuit with analog pile-up and in-Pixel ADC for high frame rate Skipper CCD-in-CMOS Sensors

The Skipper CCD-in-CMOS Parallel Read-Out Circuit V2 (SPROCKET2) is designed to enable high frame rate readout of Skipper CCD-in-CMOS image sensors. The SPROCKET2 pixel is fabricated in a 65 nm CMOS process and occupies a 60$\mu$m $\times$ 60$\mu$m footprint. SPROCKET2 is intended to be heterogeneously integrated with a pixelated Skipper CCD-in-CMOS sensor, such that one readout pixel is connected to a multiplexed array of 16 active image sensor pixels, to match their spatial geometry. Our design benefits from the Skipper CCD-in-CMOS sensor's non-destructive readout capability to achieve exceptionally low noise through multi-sampling and averaging while optimizing for total power consumption. The pixel readout utilizes correlated double sampling to minimize 1/f noise and includes "pile-up" of ten successive samples in the analog domain before digitizing at a rate of 66.7 ksps. Measurement results of in-pixel serial SAR ADC show DNL and INL of ~0. 44 LSB and 0.58 LBS respectively. A large area array of 20,000 SPROCKET2 ADC pixels (multiplexed 1:16 to 320,000 sensor pixels) is currently under test. By reading out data over a 10 Gbps optical link, this pixel design enables a frame rate of $\sim$ 4 kfps for large sensing areas with minimal sensing deadtime. In the highest gain mode, the pixelated ADC has an input-referred resolution of 10$\mu$V with a simulated power consumption of 50$\mu$W. The pixel operates with constant current draw to minimize power-rail crosstalk.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

TReactMech v4.217

TReactMech couples geomechanical processes (poroelasticity, failure, and inelastic strain) with multiphase nonisothermal flow (derived from TOUGH2) and reactive geochemical transport. At its core is the reactive-transport code TOUGHREACT v4.13. TReactMech is an efficient hybrid parallel simulator, solving the geomechanics using finite elements and MPI/PetSc, the multiphase flow using integrated finite difference and MPI/PETSc, and the reactive chemistry using OpenMP. The advantages of TReactMech are in its multiphase flow capabilities (e.g., supercritical CO2, supercritical water, air) and parallel geomechanics including full 3-D stress tensor, shear and tensile failure, coupled to porosity and permeability changes. It is backwardly compatible with TOUGH2 and TOUGHREACT v4.13, allowing for easier transitions between the codes. TReactMech can be used to simulate many natural and engineered subsurface systems, including geothermal reservoirs, borehole heat exchangers, geologic carbon sequestration, geologic storage of nuclear waste, groundwater resources, weathering, sediment diagenesis, seafloor hydrothermal circulation, hydrofracturing in unconventional reservoirs, and injection/production-induced surface deformation.

Sonnenthal, Eric↗
DOE OSTI2022

MAPPRAISER: A massively parallel map-making framework for multi-kilo pixel CMB experiments

Forthcoming cosmic microwave background (CMB) polarized anisotropy experiments have the potential to revolutionize our understanding of the Universe and fundamental physics. The sought-after, tale-telling signatures will be however distributed over voluminous data sets which these experiments will collect. These data sets will need to be efficiently processed and unwanted contributions due to astrophysical, environmental, and instrumental effects characterized and efficiently mitigated in order to uncover the signatures. This poses a significant challenge to data analysis methods, techniques, and software tools which will not only have to be able to cope with huge volumes of data but to do so with unprecedented precision driven by the demanding science goals posed for the new experiments. A keystone of efficient CMB data analysis is solvers of very large linear systems of equations. Such systems appear in very diverse contexts throughout CMB data analysis pipelines, however they typically display similar algebraic structures and can therefore be solved using similar numerical techniques. Linear systems arising in the so-called map-making problem are one of the most prominent and common ones. In this work we present a massively parallel, flexible and extensible framework, comprised of a numerical library, MIDAPACK, and a high level code, MAPPRAISER, which provide tools for solving efficiently such systems. Here, the framework implements iterative solvers based on conjugate gradient techniques: enlarged and preconditioned using different preconditioners. We demonstrate the framework on simulated examples reflecting basic characteristics of the forthcoming data sets issued by ground-based and satellite-borne instruments, executing it on as many as 16,384 compute cores. The software is developed as an open source project freely available to the community at: https://github.com/B3Dcmb/midapack.

79 ASTRONOMY AND ASTROPHYSICS↗