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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High-dimensional multi-fidelity Bayesian optimization for quantum control

Abstract We present the first multi-fidelity Bayesian optimization (BO) approach for solving inverse problems in the quantum control of prototypical quantum systems. Our approach automatically constructs time-dependent control fields that enable transitions between initial and desired final quantum states. Most importantly, our BO approach gives impressive performance in constructing time-dependent control fields, even for cases that are difficult to converge with existing gradient-based approaches. We provide detailed descriptions of our machine learning methods as well as performance metrics for a variety of machine learning algorithms. Taken together, our results demonstrate that BO is a promising approach to efficiently and autonomously design control fields in general quantum dynamical systems.

Computer Science↗
DOE OSTI2024

Biochemical Characterization of Rice Xylan Biosynthetic Enzymes in Determining Xylan Chain Elongation and Substitutions

Abstract Grass xylan consists of a linear chain of β-1,4-linked xylosyl residues that often form domains substituted only with either arabinofuranose (Araf) or glucuronic acid (GlcA)/methylglucuronic acid (MeGlcA) residues, and it lacks the unique reducing end tetrasaccharide sequence found in dicot xylan. The mechanism of how grass xylan backbone elongation is initiated and how its distinctive substitution pattern is determined remains elusive. Here, we performed biochemical characterization of rice xylan biosynthetic enzymes, including xylan synthases, glucuronyltransferases and methyltransferases. Activity assays of rice xylan synthases demonstrated that they required short xylooligomers as acceptors for their activities. While rice xylan glucuronyltransferases effectively glucuronidated unsubstituted xylohexaose acceptors, they transferred little GlcA residues onto (Araf)-substituted xylohexaoses and rice xylan 3-O-arabinosyltransferase could not arabinosylate GlcA-substituted xylohexaoses, indicating that their intrinsic biochemical properties may contribute to the distinctive substitution patterns of rice xylan. In addition, we found that rice xylan methyltransferase exhibited a low substrate binding affinity, which may explain the partial GlcA methylation in rice xylan. Furthermore, immunolocalization of xylan in xylem cells of both rice and Arabidopsis showed that it was deposited together with cellulose in secondary walls without forming xylan-rich nanodomains. Together, our findings provide new insights into the biochemical mechanisms underlying xylan backbone elongation and substitutions in grass species.

Cell Biology↗
DOE OSTI2023

Symmetry breaking/symmetry preserving circuits and symmetry restoration on quantum computers

In this article, we discuss some aspects related to the symmetries of a quantum many-body problem when trying to treat it on a quantum computer. Several features related to symmetry conservation, symmetry breaking, and possible symmetry restoration are reviewed. After briefly discussing some of the standard symmetries relevant for many-particle systems, we discuss the advantage of encoding some symmetries directly in quantum ansätze, especially to reduce the quantum register size. It is, however, well-known that the use of symmetry-breaking states can also be a unique way to incorporate specific internal correlations when a spontaneous symmetry breaking occurs. These aspects are discussed in the quantum computing context. Ultimately, an accurate description of quantum systems can be achieved only when the initially broken symmetries are properly restored. We review several methods explored previously to perform symmetry restoration on a quantum computer, for instance, the ones based on symmetry filtering by quantum phase estimation and by an iterative independent set of Hadamard tests. We propose novel methods that pave the new directions to perform symmetry restoration, like those based on the purification of the state employing the linear combination of unitaries (LCU) approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Longitudinal analysis of host protein serum signatures of treatment and recovery in pulmonary tuberculosis

A better understanding of treatment progression and recovery in pulmonary tuberculosis (TB) infectious disease is crucial. This study analyzed longitudinal serum samples from pulmonary TB patients undergoing interventional treatment to identify surrogate markers for TB-related outcomes. Serum that was collected at baseline and 8, 17, 26, and 52 weeks from 30 TB patients experiencing durable cure were evaluated and compared using a sensitive LC-MS/MS proteomic platform for the detection and quantification of differential host protein signatures relative to timepoint. The global proteome signature was analyzed for statistical differences across the time course and between disease severity and treatment groups. A total of 676 proteins showed differential expression in the serum over these timepoints relative to baseline. Comparisons to understand serum protein dynamics at 8 weeks, treatment endpoints at 17 and 26 weeks, and post-treatment at 52 weeks were performed. The largest protein abundance changes were observed at 8 weeks as the initial effects of antibiotic treatment strongly impacted inflammatory and immune modulated responses. However, the largest number of proteome changes was observed at the end of treatment time points 17 and 26 weeks respectively. Post-treatment 52-week results showed an abatement of differential proteome signatures from end of treatment, though interestingly those proteins uniquely significant at post-treatment were almost exclusively downregulated. Patients were additionally stratified based upon disease severity and compared across all timepoints, identifying 461 discriminating proteome signatures. These proteome signatures collapsed into discrete expression profiles with distinct pathways across immune activation and signaling, hemostasis, and metabolism annotations. Insulin-like growth factor (IGF) and Integrin signaling maintained a severity signature through 52 weeks, implying an intrinsic disease severity signature well into the post-treatment timeframe. Previous proteome studies have primarily focused on the 8-week timepoint in relation to culture conversion status. While this study confirms previous observations, it also highlights some differences. The inclusion of additional end of treatment and post-treatment time points offers a more comprehensive assessment of treatment progression within the serum proteome. Examining the expression dynamics at these later time periods will help in the investigation of relapse patients and has provided indicative markers of response and recovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Microwave Cast Material Examination

Microwave-cast material dating from the latest prototype development period and subsequent TRL 7 advancement testing was sent to LANL for additional characterization. The initial characterization described here is considered a supplement to and verification of that performed by Y-12 during the Technology Readiness Assessment process. The carbon chemistry results from Y-12 and LANL regarding early prototype microwave cast test object (CTO) and cylinder castings match within expectations. Only one fully intact as-cast CTO was available for examination in which carbon chemistry does not appear to vary spatially, at least at relatively low carbon levels (hypoeutectic). The large as-cast grain size leads to relatively poor grain size statistics and similar difficulties were encountered during the TRA. Small, isolated gas pores were observed in four of the five metallographic samples in prototype CTO casting PT-01. Finally, the next phase of characterization work, which focuses on corrosion behavior, has started and is described briefly.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fracture toughness evaluations for spent nuclear fuel dry storage canister welds and spent nuclear fuel clad-pellet structures

Integrity of spent nuclear fuel (SNF) interim storage canisters is very important to the safety of the back-end nuclear fuel cycle. Stress corrosion cracking (SCC) potential of interim storage canister has been considered as a high priority. Because no post-weld heat treatment was required for forming these canisters, the high tensile residual stress existed within these canister welds. This can change the fracture resistance capacity significantly as well as increase SCC potential. Due to relative thin shell thickness of a canister weldment, the spiral notch torsion test (SNTT) method was used to estimate the canister weldment fracture toughness. SNTT was developed to measure the intrinsic fracture toughness of structural materials using small specimens. The SNTT method has been applied to a wide variety of structural materials, such as low-alloy steels, stainless steel, aluminum alloy, ceramics, concrete, and composites. The SNTT system operates by applying pure torsion to cylindrical specimens with a notch line that spirals around the specimen at a 45° pitch. In order to carry out pure torsion load mode, biaxial tension/torsion tester was developed accordingly to perform SNTT protocol. Moreover, applying fracture mechanics approach to SNF system reliability investigation is warranted due to the inherent flaws and hydride structures existed in a SNF system after nuclear reactor operation. However, none of the existing fracture toughness data deal with fuel cladding specific geometry or spent fuel material conditions, such as cladding structure with the pellet-inserts and the associated pellet clad mechanical interactions induced mixed-mode damage mechanisms. Thus, the development of an intrinsic fracture mechanics approach that is suitable for SNF materials is needed. Furthermore, due to thin wall and small dimension of clad tubing structure, the SNTT method was used to estimate the clad tubing structure fracture toughness. Fracture testing were performed on the received stainless steel canister weldment, most SNTT weld samples fracture initiation sites are at heat-affected zone (HAZ) regions. The estimated fracture toughness J Q ’ for the baseline SS304 steel is at 283 kJ/m². The estimated JQ’ for the SS304/308 weld and baseline metals are 148 kJ/m 2 and 459 kJ/m 2 , respectively. Out of cell fracture testing for spent fuel structure were carried out on the surrogate rods made of Zr-4 clad and alumina inserts, the estimated fracture toughness values for baseline Zr-4 cladding with alumina-pellet inserts are: (1) For SNTT samples with a short or medium crack length, between 5.4-mm and 8-mm, the estimate J IQ upon fracture initiation for the baseline Zr-4 cladding is at 50 kJ/m 2 with 2-sigma uncertainty of 3.26 kJ/m 2 , and the associated K IQ is at 67.46 MPa$\sqrt{m}$; and (2) For SNTT samples with a long crack length, around 13-mm, the crack initialization is deviated from that of the Mode-I tensile fracture and appears to be a mixed-mode fracture of Mode I - tensile stress and Mode III - out of plane shear stress; the estimated J MQ is at 18.9 kJ/m 2 , the associated K MQ is at 41.4 MPa$\sqrt{m}$.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities

Improvements in process monitoring and control at water resource recovery facilities (WRRFs) could result in reductions in electricity consumption, chemical inputs, and greenhouse gas emissions, as well as improved energy recovery. Many current WRRF data collection, monitoring, and control approaches use 20th century process monitoring and control systems, which require large design safety factors to ensure reliability in the absence of more advanced, precise controls. Implementation of more modern data-driven control tools could lead to more efficient operations that provide intrinsic reliability with better overall process performance at full-scale. This presentation provides an overview of a recently initiated project "Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities" which will (1) develop and demonstrate data-driven process controls at full-scale facilities for five promising WRRF Applications (i.e., process technologies) that provide whole-plant approaches and offer substantial energy and resource recovery benefits, and (2) create a toolbox of new process control approaches and an implementation guide including five examples for application at utilities. The presentation also provides a detailed overview of the research approach and progress being made on one of the five Applications, namely Application 2: Biological Nutrient Removal (BNR): ammonium-based aeration control (ABAC) / ammonia vs. NOx (AvN) + partial denitration with anammox (PdNA), which is being implemented at Hampton Roads Sanitation District. This project is a collaboration of work being conducted by DC Water, Hampton Roads Sanitation District, Metro Water Recovery, University of Michigan, Northwestern University, US Military Academy - West Point, Black & Veatch, and Oak Ridge National Laboratory. Research partner: U.S. Department of Energy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Updates to Improve the Evaluated Nuclear Data of Copper Isotopes in the Resolved and Unresolved Resonance Regions

The evaluated nuclear data of the 63,65 Cu isotopes have been updated in the resolved and unresolved resonance energy regions with the goal of improving the fidelity between calculated and measured critical benchmarks. Particular focus was devoted to the 63 Cu(n, γ) cross sections because of their large sensitivity to the reactivity in the benchmark calculations. By focusing on these cross sections, the set of parameters in both resolved and unresolved resonance regions were fitted to available experimental data. The newly updated evaluations were compared to the currently available ENDF/B-VIII.0 evaluations in reactivity calculations for copper-sensitive integral benchmarks. An initial study of the sensitivity of the benchmarks to the angular distributions was performed, finding it necessary to describe the angular distributions more accurately above 100 keV. This investigation uncovered the need for more accurate data for the 63 Cu(n, γ) cross section above 100 keV. An increase in the capture cross section was found to improve agreement for the considered benchmarks.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Results of Oklo Diffusion Couple Experiments

Through the Gateway for Accelerated Innovation in Nuclear (GAIN) initiative, the U.S. Department of Energy funded a GAIN Nuclear Energy Voucher to perform out-of-pile experiments related to the fuel design for Oklo Inc., headquartered in Santa Clara, CA. GAIN’s goal is to accelerate the innovation and application of advanced nuclear technologies, and voucher recipients do not receive direct financial awards but are provided access to national laboratory capabilities at no cost. This report documents the results of diffusion couple experiments performed as part of the GAIN-funded project for Oklo. This work addresses the specific problem of filling the gap in understanding of the fuel-cladding chemical interaction (FCCI) that result from the past focus on a particular fuel design. These knowledge and mechanistic modeling gaps make it difficult to extrapolate from prior fuel performance data to advance an economically competitive fuel design. Specifically, the current state-of-the-art fuel performance modeling cannot separate the entangled effects of temperature ranges, burnups, materials, and geometries.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Development Of Non-Invasive Beam Diagnostics By Quantum Optics-Based Detection

We report our effort and latest progress developing diagnostics using quantum optics-based detection method for determining the spatial properties and current of electron beams. As electrons pass through a dilute vapor of rubidium atoms, their magnetic field perturb the atomic spin’s quantum state and causes polarization rotation of a laser resonant with an optical transition of the atoms. By measuring the polarization rotation angle across the laser beam, we recreate a 2D projection of the magnetic field and use it to determine the e-beam position, size and total current. We tested this method for an e-beam with currents ranging from 30 to 110 µA. Our study shows this approach is insensitive to electron kinetic energy, and is initially verified experimentally between 10 to 20 keV. A different approach was also performed with highly excited rubidium atoms in Rydberg states through a coherent two photon process. We use this detection scheme to measure the electric field generated by a

Zhang, S. [Thomas Jefferson National Accelerator F↗
DOE OSTI2023

Investigation of microorganisms in cannabis after heating in a commercial vaporizer

There are concerns about microorganisms present on cannabis materials used in clinical settings by individuals whose health status is already compromised and are likely more susceptible to opportunistic infections from microbial populations present on the materials. Most concerning is administration by inhalation where cannabis plant material is heated in a vaporizer, aerosolized, and inhaled to receive the bioactive ingredients. Heating to high temperatures is known to kill microorganisms including bacteria and fungi; however, microbial death is dependent upon exposure time and temperature. It is unknown whether the heating of cannabis at temperatures and times designated by a commercial vaporizer utilized in clinical settings will significantly decrease the microbial loads in cannabis plant material. To assess this question, bulk cannabis plant material supplied by National Institute on Drug Abuse (NIDA) was used to assess the impact of heating by a commercial vaporizer. Initial method development studies using a cannabis placebo spiked with Escherichia coli were performed to optimize culture and recovery parameters. Subsequent studies were carried out using the cannabis placebo, low delta-9 tetrahydrocannabinol (THC) potency and high THC potency cannabis materials exposed to either no heat or heating for 30 or 70 seconds at 190°C. Phosphate-buffered saline was added to the samples and the samples agitated to suspend the microorganism. Microbial growth after no heat or heating was evaluated by plating on growth media and determining the total aerobic microbial counts and total yeast and mold counts. Overall, while there were trends of reductions in microbial counts with heating, these reductions were not statistically significant, indicating that heating using standard vaporization parameters of 70 seconds at 190°C may not eliminate the existing microbial bioburden, including any opportunistic pathogens. When cultured organisms were identified by DNA sequence analyses, several fungal and bacterial taxa were detected in the different products that have been associated with opportunistic infections or allergic reactions including Enterobacteriaceae, Staphylococcus, Pseudomonas, and Aspergillus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Ni-H-Beta Catalysts for Ethylene Oligomerization: Impact of Parent Cation on Ni Loading, Speciation, and Siting

Ni-H-Beta catalysts for ethylene oligomerization (EO) were prepared by ion exchange of NH 4 -Beta and H-Beta zeolites with aqueous Ni(NO 3 ) 2 and characterized by H 2 -temperature-programmed reduction (TPR), NH 3 -temperature-programmed desorption (TPD), and diffuse-reflectance infrared Fourier-transform spectroscopy (DRIFTS). Quadruple exchange of NH 4 -Beta at 70 °C resulted in 2.5 wt.% Ni loading corresponding to a Ni 2+ /framework aluminum (FAl) molar ratio of 0.52. [NiOH] + and H + are the primary charge-compensating cations in the uncalcined catalyst, as evidenced by TPR and DRIFTS. Subsequent calcination at 550 °C in air yielded a Ni-H-Beta catalyst containing primarily bare Ni 2+ ions bonded to framework oxygens. Quadruple exchange of H-Beta at 70 °C gave 2.0 wt.% Ni loading (Ni 2+ /FAl = 0.41). After calcination at 550 °C, the resulting Ni-H-Beta catalyst comprises a mixture of bare Ni 2+ ions: [NiOH] + and NiO species. The relative abundance of [NiOH] + increases with the number of exchanges. In situ pretreatment at 500 °C in flowing He converted the [NiOH] + species to bare Ni 2+ ions via dehydration. The bare Ni 2+ ions interact strongly with the Beta framework as evidenced by a perturbed antisymmetric T-O-T vibration at 945 cm -1 . DRIFT spectra of CO adsorbed at 20 °C indicate that the Ni 2+ ions occupy two distinct exchange positions. The results of EO testing at 225 °C and 11 bar (ethylene) suggested that the specific Ni 2+ species initially presented (e.g., bare Ni 2+ , [NiOH] + ) did not significantly affect the catalytic performance.

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

The Role of Oxygen Concentration in Enabling High Gradients in Niobium SRF Cavities

We studied the role of O concentration with depth in the performance of Nb SRF cavities. An ensemble of electropolished 1.3 GHz cavities, which initially showed high field Q-slope (HFQS), was subjected to sequential testing and treatment with in-situ low temperature baking at various temperatures. We find that increasing the bake duration causes (i) an increase in the onset of HFQS until it is absent up to quench (ii) a non-monotonic relationship with the quench field (iii) an evolution of the RBCS toward a non-equilibrium behavior that drives anti-Q slope. Our data is qualitatively explained by assuming an O diffusion model and suggests that the mitigation of HFQS that arises from 120 C in-situ LTB is mediated by the diffusion of O from the native oxide which prevents the precipitation of proximity-coupled Nb nano-hydrides, in turn enabling higher quench fields. The decrease in quench field for cavities in which O has been diffused >90 nm from the RF surface may be due to a reduction of the field limit in the SS bilayer structure. We also suggest that the evolution of the RBCS occurs due to the absence of proximity coupled inclusions, bringing about non-equilibrium effects.

Bafia, D.↗
DOE OSTI2020

Development of a Reference Design for a Cyber-Physical System

The purpose of this thesis is to develop a reference design to assist in the selection of security practices in power electronics design. A prototype will be developed from this reference design for evaluation. This evaluation will include a brief cost/benefit analysis to gauge the efficacy of implementing each layer of security throughout the power electronics design process. This thesis will also describe the obstacles and effectiveness of integrating a Trusted Platform Module (TPM) into a cyber-hardened grid-connected device. The TPM device is a secured crypto processor that assists in generating, storing, and restricting the use of cryptographic keys. The emphasis of this research is to establish integrity, authenticity, and confidentiality within a system by providing a baseline of security concerns for segments of the system. This research considers communication, control, and hardware level securities. The scope of this thesis will review the necessary security methods as well as consider the effects these methods have on the embedded system, to assess the desired security to responsiveness trade off. Applying this approach to a design process will alleviate various unknowns of appending security to a power electronics design. This thesis describes the specific vulnerabilities introduced within this grid-edge environment, and how the liabilities within the system can be mitigated. Initially, common security techniques will be considered to establish a guideline to benchmark performance and resource costs of the system. The foundation will be a non-hardened power electronic system platform with industry standard communication protocols. Several security techniques and attack vectors will then be evaluated to contribute to the base level platform. Other fail-safe features take place to gauge progress of the selected approach, non-inclusive to the TPM. Collectively, this investigation will determine a valid experiment by appraising and categorizing resource allocation, performance overhead, and monetary cost analysis results into a reference design. The prototype will then demonstrate methods to relieve common threats that are purposefully implemented into the design.

Blair, Nicholas Paul↗
DOE OSTI2024

Multiphysics Demonstration of Temperature-Driven Assembly Bowing in SFRs using MOOSE-Based Codes

Core bowing is an important passive safety mechanism in liquid metal cooled fast reactors. When the core restraint system is properly designed, temperature and flux gradients influence assemblies in the core to bow into less reactive configurations during accident scenarios, resulting in negative reactivity feedback. Prediction of core bowing involves complex interplay of radiation transport, impacts of fluid flow and heat transfer on duct temperature, and mechanical responses to the induced temperature and flux gradients. Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program [1], an integrated multiphysics approach is being developed to model the core bowing phenomena in liquid metal-cooled fast reactors with the Multiphysics Object Oriented Simulation Environment (MOOSE) [2]. In this methodology, the MOOSE-based reactor physics code Griffin [3] will solve the neutron transport equation and determine the power distribution. With the detailed power distribution from Griffin, the subchannel analysis codes MOOSE-Subchannel [4] and Pronghorn [5] are utilized to calculate the assembly temperature distribution. MOOSE’s Solid Mechanics [6] and Contact [7] Modules are leveraged to calculate the thermal expansion and duct bowing displacement with the duct wall temperature from thermal hydraulics calculation. In this work, an initial one-way coupling demonstration of the integrated multiphysics approach has been performed on a seven-assembly problem based on the sodium-cooled fast reactor ABR-1000 design [8]. The neutronics calculation with Griffin is not yet involved in the current simulation. MOOSE-Subchannel and Pronghorn evaluate fluid and solid temperature based on a fixed power distribution. In addition, one-way coupling is utilized in this coupled calculation, via Pronghorn passing the duct temperature data to the MOOSE Solid Mechanics calculation. An assessment of the Solid Mechanics module was performed in parallel to verify duct bowing behavior with duct-to-duct contact phenomenon [9]. The displacement from MOOSE Solid Mechanics is not yet transferred back and utilized in the Pronghorn and MOOSE-Subchannel calculation. This model will be available on the National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB) repository [10]. Future stages of this work will involve solving problems of increasing complexity as well as adding more physics (e.g. reactor physics) to the integrated workflow to reach the end goal of modeling the core bowing phenomenon with an integrated multiphysics workflow.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Deep active learning for classifying cancer pathology reports

Abstract Background Automated text classification has many important applications in the clinical setting; however, obtaining labelled data for training machine learning and deep learning models is often difficult and expensive. Active learning techniques may mitigate this challenge by reducing the amount of labelled data required to effectively train a model. In this study, we analyze the effectiveness of 11 active learning algorithms on classifying subsite and histology from cancer pathology reports using a Convolutional Neural Network as the text classification model. Results We compare the performance of each active learning strategy using two differently sized datasets and two different classification tasks. Our results show that on all tasks and dataset sizes, all active learning strategies except diversity-sampling strategies outperformed random sampling, i.e., no active learning. On our large dataset (15K initial labelled samples, adding 15K additional labelled samples each iteration of active learning), there was no clear winner between the different active learning strategies. On our small dataset (1K initial labelled samples, adding 1K additional labelled samples each iteration of active learning), marginal and ratio uncertainty sampling performed better than all other active learning techniques. We found that compared to random sampling, active learning strongly helps performance on rare classes by focusing on underrepresented classes. Conclusions Active learning can save annotation cost by helping human annotators efficiently and intelligently select which samples to label. Our results show that a dataset constructed using effective active learning techniques requires less than half the amount of labelled data to achieve the same performance as a dataset constructed using random sampling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Blast furnace slag reactions in various solutions (Interim Report)

Blast furnace slag (BPS) is a critical component of grout formulations for the remediation of low activity nuclear waste. This interim report describes the initial results of a study designed to investigate the fundamental mechanisms of BPS dissolution. The goal of the work is to delineate the physicochemical aspects of the slag that impart beneficial properties to grout formulations to enable the consistent production of a slag-replacement material (“designer slag”) that performs better than what is commercially available. This report documents the dissolution experiments that were conducted using nine different initial solution compositions. Solution measurements for each solution, including pH and solution composition, are given for 1, 7, 14, 28, and 56 day intervals samples. Scanning electron microscopy images are presented for the 56 day samples from each of the solutions. Inferences about reaction mechanisms and 56-day mineralogy are made based on the information collected to date. Some conclusions are made based on the work performed for this interim report, and a path forward including the strategy for making stronger conclusions based on X-ray diffraction (XRD) analyses is presented.

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

Two-Step Hyperparameter Optimization Method: Accelerating Hyperparameter Search by Using a Fraction of a Training Dataset

Abstract Hyperparameter optimization (HPO) is an important step in machine learning (ML) model development, but common practices are archaic—primarily relying on manual or grid searches. This is partly because adopting advanced HPO algorithms introduces added complexity to the workflow, leading to longer computation times. This poses a notable challenge to ML applications, as suboptimal hyperparameter selections curtail the potential of ML model performance, ultimately obstructing the full exploitation of ML techniques. In this article, we present a two-step HPO method as a strategic solution to curbing computational demands and wait times, gleaned from practical experiences in applied ML parameterization work. The initial phase involves a preliminary evaluation of hyperparameters on a small subset of the training dataset, followed by a reevaluation of the top-performing candidate models postretraining with the entire training dataset. This two-step HPO method is universally applicable across HPO search algorithms, and we argue it has attractive efficiency gains. As a case study, we present our recent application of the two-step HPO method to the development of neural network emulators for aerosol activation. Although our primary use case is a data-rich limit with many millions of samples, we also find that using up to 0.0025% of the data—a few thousand samples—in the initial step is sufficient to find optimal hyperparameter configurations from much more extensive sampling, achieving up to 135× speedup. The benefits of this method materialize through an assessment of hyperparameters and model performance, revealing the minimal model complexity required to achieve the best performance. The assortment of top-performing models harvested from the HPO process allows us to choose a high-performing model with a low inference cost for efficient use in global climate models (GCMs).

97 MATHEMATICS AND COMPUTING↗