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DOE OSTI2022

The revised FLORIDyn model: implementation of heterogeneous flow and the Gaussian wake

In this paper, a new version of the FLOw Redirection and Induction Dynamics (FLORIDyn) model is presented. The new model uses the three-dimensional parametric Gaussian FLORIS model and can provide dynamic wind farm simulations at a low computational cost under heterogeneous and changing wind conditions. Both FLORIS and FLORIDyn are parametric models which can be used to simulate wind farms, evaluate controller performance and can serve as a control-oriented model. One central element in which they differ is in their representation of flow dynamics: FLORIS neglects these and provides a computationally very cheap approximation of the mean wind farm flow. FLORIDyn defines a framework which utilizes this low computational cost of FLORIS to simulate basic wake dynamics. This is achieved by creating so-called observation points (OPs) at each time step at the rotor plane which inherit the turbine state. In this work, we develop the initial FLORIDyn framework further considering multiple aspects. The underlying FLORIS wake model is replaced by a Gaussian wake model. The distribution and characteristics of the OPs are adapted to account for the new parametric model but also to take complex flow conditions into account. To achieve this, a mathematical approach is developed to combine the parametric model and the changing, heterogeneous world conditions and link them with each OP. We also present a computationally lightweight wind field model to allow for a simulation environment in which heterogeneous flow conditions are possible. FLORIDyn is compared to Simulator for Offshore Wind Farm Applications (SOWFA) simulations in three- and nine-turbine cases under static and changing environmental conditions. The results show a good agreement with the timing of the impact of upstream state changes on downstream turbines. They also show a good agreement in terms of how wakes are displaced by wind direction changes and when the resulting velocity deficit is experienced by downstream turbines. A good fit of the mean generated power is ensured by the underlying FLORIS model. In the three-turbine case, FLORIDyn simulates 4 s simulation time in 24.49 ms computational time. The resulting new FLORIDyn model proves to be a computationally attractive and capable tool for model-based dynamic wind farm control.

17 WIND ENERGY↗

NASA NTRS1996

Risk as a Resource - A New Paradigm

NASA must change dramatically because of the current United States federal budget climate. The American people and their elected officials have mandated a smaller, more efficient and effective government. For the past decade, NASA's budget had grown at or slightly above the rate of inflation. In that era, taking all steps to avoid the risk of failure was the rule. Spacecraft development was characterized by extensive analyses, numerous reviews, and multiple conservative tests. This methodology was consistent with the long available schedules for developing hardware and software for very large, billion dollar spacecraft. Those days are over. The time when every identifiable step was taken to avoid risk is being replaced by a new paradigm which manages risk in much the same way as other resources (schedule, performance, or dollars) are managed. While success is paramount to survival, it can no longer be bought with a large growing NASA budget.

Risk Resource↗

NASA NTRS2022

A preliminary assessment of olivine phenocrysts from the monogenetic basalt of the McCartys Flow, Zuni-Bandera Volcanic Field, New Mexico

Monogenetic small-volume basaltic volcanoes are the most abundant subaerial volcanic landforms on Earth but are some of the most poorly understood systems. Their short durations, small volumes, and lack of recurrence make monitoring and hazard assessment difficult. The Zuni-Bandera volcanic field in western New Mexico contains small-volume basaltic centers erupting tholeiitic to alkalic basalts. Evidence shows no correlation of magma composition with eruption age, location, or volumetric output, prompting questions about the influence of magma ascent rates, magma storage conditions, and mantle source characteristics on lava compositions. Here, we present olivine major and minor element mineral chemistry from the 3200-year-old McCartys Flow, the youngest tholeiite basalt in the volcanic field. Olivine displays four phenocryst types with unique textures and major and minor element compositions. Multiple olivine types co-exist at the thin section scale. Major and minor element diffusion at frozen melt–phenocryst interfaces was modeled, revealing magma residence times ranging from 3–9 months. Type 3 olivine phenocrysts require step function initial conditions and record diffusion re-equilibration followed by magma mixing. These profiles indicate the magma resided in the reservoir for 10–15 years and accumulated from multiple batches of mixed magmas less than 10 days before the eruption. Our results show that primitive magmas in small-volume monogenetic volcanoes have complex lithospheric magmatic histories and stored in magma bodies influenced by an open system to develop different local chemical environments.

Gary S. Michelfelder↗

DOE OSTI2022

Distributed model predictive control for coordinated, grid-interactive buildings

Continued focus on reducing carbon emissions and improving energy efficiency requires buildings to become grid-interactive and not just behave as static consumers. A distributed model predictive control (DMPC) algorithm known as Limited-Communication (LC) DMPC is modified to enable grid-interactive buildings. A grid-aggregator subsystem is added that allows for a bulk grid power reference signal to be followed while the individual building subsystems also achieve their local comfort objectives. The LC-DMPC algorithm is applied for the first time to systems with multiple buildings. Adequate power tracking is shown for different simulation scenarios involving heterogeneous buildings, and next steps are discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2004

Using Science Driven Technologies for the Defense and Security Applications

For the past three decades, Earth science remote sensing technologies have been providing enormous amounts of useful data and information in broadening our understanding of our home planet as a system. This research, as it has expanded our learning process, has also generated additional questions. This has further resulted in establishing new science requirements, which have culminated in defining and pushing the state-of-the-art technology needs. NASA s Earth science program has deployed 18 highly complex satellites, with a total of 80 sensors, so far and is in a process of defining and launching multiple observing systems in the next decade. Due to the heightened security alert of the nation, researchers and technologists are paying serious attention to the use of these science driven technologies for dual use. In other words, how such sophisticated observing and measuring systems can be used in detecting multiple types of security concerns with a substantial lead time so that the appropriate law enforcement agencies can take adequate steps to defuse any potential risky scenarios. This paper examines numerous NASA technologies such as laser/lidar systems, microwave and millimeter wave technologies, optical observing systems, high performance computational techniques for rapid analyses, and imaging products that can have a tremendous pay off for security applications.

Habib, Shahid↗

DOE OSTI2021

COVID-19 dynamics across the US: A deep learning study of human mobility and social behavior

This paper presents a deep learning framework for epidemiology system identification from noisy and sparse observations with quantified uncertainty. The proposed approach employs an ensemble of deep neural networks to infer the time-dependent reproduction number of an infectious disease by formulating a tensor-based multi-step loss function that allows us to efficiently calibrate the model on multiple observed trajectories. The method is applied to a mobility and social behavior-based SEIR model of COVID-19 spread. The model is trained on Google and Unacast mobility data spanning a period of 66 days, and is able to yield accurate future forecasts of COVID-19 spread in 203 US counties within a time-window of 15 days. Interestingly, a sensitivity analysis that assesses the importance of different mobility and social behavior parameters reveals that attendance of close places, including workplaces, residential, and retail and recreational locations, has the largest impact on the effective reproduction number. Furthermore, the model enables us to rapidly probe and quantify the effects of government interventions, such as lock-down and re-opening strategies. Taken together, the proposed framework provides a robust workflow for data-driven epidemiology model discovery under uncertainty and produces probabilistic forecasts for the evolution of a pandemic that can judiciously provide information for policy and decision making. All codes and data accompanying this manuscript are available at https://github.com/PredictiveIntelligenceLab/DeepCOVID19.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Multimodal Analysis of Reaction Pathways of Cathode Materials for Lithium Ion Batteries

Conversion mechanism in lithium ion batteries provides higher capacity than intercalation mechanism since multiple numbers of electrons and lithium ions are associated. However, poor cycling stability, large voltage hysteresis, and low energy efficiency have been great challenges of conversion reaction. To address those issues, conversion-type electrode materials have been reformed via doping or substituting other elements. For example, iron fluorides (FeF 2 , FeF 3 ) have modified as iron oxyfluorides (FeF 1-x O x ), showing enhanced long-term stability. Furthermore, co-substituted (both anion and cation substituted) Fe 0.9 Co 0.1 OF (FeCoOF) was demonstrated excellent cycling stability. (capacity of 350 mAh g -1 at a current of 500 mA g -1 for 1000 cycles). Substituting anion and cation in iron fluoride has been suggested as an effective method to achieve better reversibility but understanding of lithiation reactions in co-substituted FeCoOF is not clear. This work takes advantage of ex-situ/ in-situ synchrotron X-ray based techniques and transmission electron microscopy to elucidate structural changes with lithium ion, which may provide fundamental insights into modifying conversion-type materials. Figure 1 presents discharge-charge curves and pair distribution function patterns acquired at each potential. As lithium ions were inserted, structural changes were noticed both at short-range and long-range. However, long-range ordering was nearly maintained even at 1 V, indicating absence of conversion reaction. Figure 2 shows lithiation induced structural evolution of a single FeCoOF nanorod observed in real time. As lithiation proceeds, the width of nanorods shows a stepwise increase, particularly A in figure 2d, which may indicate multiple steps of lithiation occur. Considering that conversion reaction takes place around 2 V in FeF 3 , co-substitution Co and O into iron fluoride may change thermodynamic features of lithiation reactions by lowering the initiation potential for conversion reaction. Instead, phase transformations occur at long-range order, which may help maintaining structural integrity during operation, eventually, achieving cycling stability.

25 ENERGY STORAGE↗

DOE OSTI2026

Postirradiation Examination of WIRE-21 Experiment Irradiated in the High Flux Isotope Reactor

Westinghouse Electric Company is developing wireless sensors to monitor the centerline temperature and internal pressure of commercial light-water reactor fuel rods during irradiation. Oak Ridge National Laboratory and Westinghouse Electric Company developed the Wireless Instrumented RB Experiment 2021 (WIRE-21) to test wireless temperature and pressure sensor technologies in a removable beryllium position in the High Flux Isotope Reactor. The experiment was irradiated for a total of 75 days, at temperatures ranging from approximately 150°C to 400°C, resulting in a peak fast (energy > 0.1 MeV) neutron fluence of about 3 × 10 21 n/cm 2 . The temperature was intentionally cycled multiple times to compare the response of the wireless temperature sensor to collocated thermocouples. Similarly, the pressure sensor was actuated in multiple steps to compare the response of the wireless measurement to excore pressure transducers (Petrie et al., 2023). After irradiation, the experiment was disassembled in the Irradiated Fuels Examination Laboratory (IFEL) hot cell at Oak Ridge National Laboratory with the intent to recover sensor and dosimetry components, document the as-irradiated condition of the hardware, and investigate possible causes of the sensor behavior observed during irradiation. The postirradiation examination successfully recovered and preserved key WIRE-21 components. After the housing was removed using a milling machine, the internal experiment sections were examined. All eight fiber-optic sensors were recovered, cut, and stored. The silicon carbide thermometry, temperature sensor, pressure sensor, lower spacer, and selected pressure and temperature cable sections were also removed and stored. The metal bellows of the pressure sensor was found to be plastically deformed, indicating that it had been properly pressurized during irradiation and generally behaved as expected. X-ray diffraction analysis of a section of one of the irradiated inductor cores within the pressure sensor was performed and confirmed the presence of phase-pure alpha ferrite (i.e., no unexpected phase transformations). Inductance testing was performed on the irradiated pressure sensor cores using an unirradiated test coil, and DC resistance measurements of the transceiver coils were also performed. The measurements with irradiated inductor cores assembled inside unirradiated coils showed slightly reduced inductance compared to measurements made with unirradiated cores, but the difference was not sufficient to explain the more significant reductions in inductance that were observed in-pile. Therefore, it is suspected that degradation of the inductor coils (specifically the wire wrapping) is responsible for the reduced inductance observed in-pile.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

PARA: A New Platform for the Rapid Assembly of gRNA Arrays for Multiplexed CRISPR Technologies

Multiplexed CRISPR technologies have great potential for pathway engineering and genome editing. However, their applications are constrained by complex, laborious and time-consuming cloning steps. In this research, we developed a novel method, PARA, which allows for the one-step assembly of multiple guide RNAs (gRNAs) into a CRISPR vector with up to 18 gRNAs. Here, we demonstrate that PARA is capable of the efficient assembly of transfer RNA/Csy4/ribozyme-based gRNA arrays. To aid in this process and to streamline vector construction, we developed a user-friendly PARAweb tool for designing PCR primers and component DNA parts and simulating assembled gRNA arrays and vector sequences.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance

This study focuses on the performance of the elastic–viscous–plastic (EVP) dynamical solver within the sea ice model, CICE v6.5.1. The study has been conducted in two steps. First, the standard EVP solver was extracted from CICE for experiments with refactored versions, which are used for performance testing. Second, one refactored version was integrated and tested in the full CICE model to demonstrate that the new algorithms do not significantly impact the physical results. The study reveals two dominant bottlenecks, namely (1) the number of Message Parsing Interface (MPI) and Open Multi-Processing (OpenMP) synchronization points required for halo exchanges during each time step combined with the irregular domain of active sea ice points and (2) the lack of single-instruction, multiple-data (SIMD) code generation. The standard EVP solver has been refactored based on two generic patterns. The first pattern exposes how general finite differences on masked multi-dimensional arrays can be expressed in order to produce significantly better code generation by changing the memory access pattern from random access to direct access. The second pattern takes an alternative approach to handle static grid properties. The measured single-core performance improvement is more than a factor of 5 compared to the standard implementation. The refactored implementation of strong scales on the Intel® Xeon® Scalable Processors series node until the available bandwidth of the node is used. For the Intel® Xeon® CPU Max series, there is sufficient bandwidth to allow the strong scaling to continue for all the cores on the node, resulting in a single-node improvement factor of 35 over the standard implementation. This study also demonstrates improved performance on GPU processors.

58 GEOSCIENCES↗

NASA NTRS1989

Flux-vector splitting for unsteady calculations on dynamic meshes

The method of flux vector splitting used is that of Van Leer. The fluxes split in this manner have the advantage of being continuously differentiable at eigenvalue sign changes and this allows normal shocks to be captured with at most two interior zones, although in practice only one zone is usually observed. The fluxes as originally derived, however did not include the necessary terms appropriate for calculations on a dynamic mesh. The extension of the splitting to include these terms while retaining the advantages of the original splitting is the main purpose of this investigation. In addition, the use of multiple grids to reduce the computer time is investigated. A subiterative procedure to eliminate factorization and linearization error so that larger time steps can be used is also investigated.

Anderson, W. Kyle↗

NASA NTRS1991

Lanczos eigensolution method for high-performance computers

The theory, computational analysis, and applications are presented of a Lanczos algorithm on high performance computers. The computationally intensive steps of the algorithm are identified as: the matrix factorization, the forward/backward equation solution, and the matrix vector multiples. These computational steps are optimized to exploit the vector and parallel capabilities of high performance computers. The savings in computational time from applying optimization techniques such as: variable band and sparse data storage and access, loop unrolling, use of local memory, and compiler directives are presented. Two large scale structural analysis applications are described: the buckling of a composite blade stiffened panel with a cutout, and the vibration analysis of a high speed civil transport. The sequential computational time for the panel problem executed on a CONVEX computer of 181.6 seconds was decreased to 14.1 seconds with the optimized vector algorithm. The best computational time of 23 seconds for the transport problem with 17,000 degs of freedom was on the the Cray-YMP using an average of 3.63 processors.

Bostic, Susan W.↗

NASA NTRS2006

Steps Toward Optimal Competitive Scheduling

This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum of users preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum ofsers preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.

Frank, Jeremy↗

DOE OSTI2023

Writing the Programs of Programmable Catalysis

It has long been known that non-steady state and periodic catalytic reactor operation in terms of temperature, pressure, and composition can lead to higher overall productivity and/or product selectivity than the best steady operation. Recently, the emergence of catalysts whose intrinsic properties can be made to oscillate with time, introduces advanced forcing capabilities that can be “programmed” into the catalysts to broaden the scope and applicability of periodic operation to surface chemistry. In this work, an algorithmic approach is implemented to significantly accelerate the discovery and optimization of periodic steady states of catalytic reactors. Decomposition of complex dynamics into fundamental mechanistic fast–slow steps is seen to improve conceptual understanding of the relationship between binding energy oscillation protocols and overall catalytic rates. Finding structured forcing protocols, optimally tailored to the multiple time scales of a given individual mechanism, requires an efficient search of high-dimensional parameter spaces. Here, this is enabled here through active learning (Bayesian optimization, enhanced by our proposed Bayesian continuation). Implementation of these methods is shown to accelerate the evaluation of catalyst programs by up to several orders of magnitude. Faster screening of programmable catalysts to discover periodic steady states enables the optimization of catalytic operating protocols and thus opens the possibility for catalyst engineering based on optimal forcing programs to control rate and product selectivity, even for complex multistep catalytic mechanisms.

catalysis↗

DOE OSTI2025

Macro-level mechanical interlocking: A rapid joining approach for additively manufactured compression molded composite panels

Composite joining typically involves multiple steps, such as drilling and surface treatment, as part of the manufacturing process, which leads to low throughput and long cycle times. In the present study, we demonstrated a macro-level mechanical interlocking (MI) based, rapid joining technique to assemble additively manufactured compression molded (AMCM) panels, enabling the production of parts larger than the mold dimensions. Composite panels made of 20 wt% short carbon fiber reinforced acrylonitrile butadiene styrene (CF/ABS) were joined using MI features of various geometries, namely tree (TR), dovetail (Dov), rectangle 2 (Rect2), and rectangle 1 (Rect1), and their in-plane strength was evaluated. The resultant strength of the tested MI joints reached up to 74 % of the baseline tensile strength (i.e., the ‘no joint’ case). Observations from optical and scanning electron microscopy revealed inadequate polymer diffusion between the adherends, indicating that the joint strength was primarily derived from mechanical interlocking. Additionally, the fracture surfaces exhibited stress-whitening marks, which were characterized using differential scanning calorimetry (DSC). The increase in melting enthalpy suggested local stretching of polymer chains due to MI. Finite element analysis (FEA) indicated that the Rect1 MI feature, which generated the lowest stress concentration, outperformed the others in terms of joint strength, achieving 42 MPa. As a demonstration of the MI joining method, a battery box tray measuring 108 cm × 34 cm using a mold with an effective dimension of 36 cm × 34 cm successfully manufactured, resulting in a part with an area three times larger than the mold. In conclusion, this study presents a promising approach to improving composite joining techniques while minimizing production complexities.

In-plane joining↗

DOE OSTI2020

Dynamic re-equilibration controlled multi-step transformations in (Mn, Fe) 2 (P, Si) alloys

In (Mn, Fe) 2 (P, Si) alloys crystallographic first-order phase transformations enable strong coupling of magnetic and entropic properties, potentially leading to high-efficiency energy generation and refrigeration applications. Although hysteresis losses that limit these applications can be reduced through careful control of alloy composition, compositional tuning can also unfavorably influence transformation temperatures and magnetocaloric coupling strength. Hence, exploration of additional processing variables enabling independent control of transformation properties is crucial. In this work, we investigate the role of thermal history as an additional processing variable, exploiting thermally-activated mechanisms to control properties of non-diffusive transformations in (Mn, Fe) 2 (P, Si) alloys. In so doing, we report an unusual transformation-splitting phenomenon following annealing at intermediate times, where a single well-defined magneto-structural transformation evolves towards a multi-step transformation with individual steps occurring at multiple distinct temperatures. Here, on longer annealing at the same temperatures, single-step transformation behavior is recovered. Through additional magnetic and crystallographic characterization, we show that the thermal history-controlled multi-step behavior results from sluggish thermally-activated diffusion. The two-step transformation corresponds to non-equilibrium bimodal composition distributions in the transforming phase, and these develop through a dynamic re-equilibration process as the alloy passes relatively slowly between different thermal equilibria. Together, these results suggest that thermal history primarily controls the transformation properties of (Mn, Fe) 2 (P, Si) alloys indirectly through the composition of one or more transforming phases. Additional investigations are needed to develop thermal history processing for decoupling hysteresis control from other transformation properties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1987

Unsteady transonic flow calculations for realistic aircraft configurations

A transonic unsteady aerodynamic and aeroelasticity code has been developed for application to realistic aircraft configurations. The new code is called CAP-TSD which is an acronym for Computational Aeroelasticity Program - Transonic Small Disturbance. The CAP-TSD code uses a time-accurate approximate factorization (AF) algorithm for solution of the unsteady transonic small-disturbance equation. The AF algorithm is very efficient for solution of steady and unsteady transonic flow problems. It can provide accurate solutions in only several hundred time steps yielding a significant computational cost savings when compared to alternative methods. The new code can treat complete aircraft geometries with multiple lifting surfaces and bodies including canard, wing, tail, control surfaces, launchers, pylons, fuselage, stores, and nacelles. Applications are presented for a series of five configurations of increasing complexity to demonstrate the wide range of geometrical applicability of CAP-TSD. These results are in good agreement with available experimental steady and unsteady pressure data. Calculations for the General Dynamics one-ninth scale F-16C aircraft model are presented to demonstrate application to a realistic configuration. Unsteady results for the entire F-16C aircraft undergoing a rigid pitching motion illustrated the capability required to perform transonic unsteady aerodynamic and aeroelastic analyses for such configurations.

Batina, John T.↗

NASA NTRS1987

Unsteady transonic flow calculations for realistic aircraft configurations

Batina, John T.↗