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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Developing multi-gene CRISPRa/i programs to accelerate DBTL cycles in ABF hosts engineered for chemical production

This project developed and implemented a modular CRISPR activation and interference (CRISPRa/i) platform to accelerate strain optimization and pathway development for industrially relevant microbial hosts. By integrating multiplexed transcriptional perturbation tools with data-driven Design–Build–Test–Learn (DBTL) workflows, the team achieved reductions in cycle time and enhanced production of industrial aromatics, particularly 4-aminocinnamic acid (4-ACA), in Pseudomonas putida. Key accomplishments included: ● Development of a robust, tunable CRISPRa/i system in P. putida that enabled efficient multi-target gene regulation via guide RNA (gRNA) programs ● Completion of two full DBTL cycles, guided by machine learning (ML) models trained on transcriptomic and performance data, reducing engineering time by over 30% ● Optimization of multi-gene regulatory programs to balance expression of host and pathway modules, improve 4-ACA titers, and resolve metabolic bottlenecks ● Demonstration of system portability through a limited proof-of-concept extension in Acinetobacter baylyi, underscoring the generalizability of the approach ● Evaluation of strain performance on lignocellulosic biomass-derived substrates, demonstrating the feasibility of converting renewable carbon into aromatic building blocks These results illustrate the feasibility of applying ML-guided CRISPRa/i perturbation strategies to accelerate strain development in complex microbial systems. The resulting tools and datasets contribute to DOE objectives by improving platform predictability, reducing development costs, and enabling broader access to sustainable, economically viable bioproduction technologies.

09 BIOMASS FUELS↗
DOE OSTI2022

The SODA Approach: Leveraging High-Level Synthesis for Hardware/Software Co-design and Hardware Specialization: Invited

Novel "converged" applications combine phases of scientific simulation with data analysis and machine learning. Each computational phase can benefit from specialized accelerators. However, algorithms evolve so quickly that mapping them on existing accelerators is suboptimal or even impossible. This paper presents the SODA (Software Defined Accelerators) framework, a modular, multi-level, open-source, no-human-in-the-loop, hardware synthesizer that enables end-to-end generation of specialized accelerators. SODA is composed of SODA-Opt, a high-level frontend developed in MLIR that interfaces with domain-specific programming frameworks and allows performing system level design, and Bambu, a state-of-the-art high-level synthesis engine that can target different device technologies. The framework implements design space exploration as compiler optimization passes. We show how the modular, yet tight, integration of the high-level optimizer and lower-level HLS tools enables the generation of accelerators optimized for the computational patterns of converged applications. We then discuss some of the research opportunities that such a framework allows, including system-level design, profile driven optimization, and supporting new optimization metrics.

Bohm Agostini, Nicolas↗
NASA NTRS2014

Validation of the 5th and 95th Percentile Hybrid III Anthropomorphic Test Device Finite Element Model

NASA spacecraft design requirements for occupant protection are a combination of the Brinkley criteria and injury metrics extracted from anthropomorphic test devices (ATD's). For the ATD injury metrics, the requirements specify the use of the 5th percentile female Hybrid III and the 95th percentile male Hybrid III. Furthermore, each of these ATD's is required to be fitted with an articulating pelvis and a straight spine. The articulating pelvis is necessary for the ATD to fit into spacecraft seats, while the straight spine is required as injury metrics for vertical accelerations are better defined for this configuration. The requirements require that physical testing be performed with both ATD's to demonstrate compliance. Before compliance testing can be conducted, extensive modeling and simulation are required to determine appropriate test conditions, simulate conditions not feasible for testing, and assess design features to better ensure compliance testing is successful. While finite element (FE) models are currently available for many of the physical ATD's, currently there are no complete models for either the 5th percentile female or the 95th percentile male Hybrid III with a straight spine and articulating pelvis. The purpose of this work is to assess the accuracy of the existing Livermore Software Technology Corporation's FE models of the 5th and 95th percentile ATD's. To perform this assessment, a series of tests will be performed at Wright Patterson Air Force Research Lab using their horizontal impact accelerator sled test facility. The ATD's will be placed in the Orion seat with a modified-advanced-crew-escape-system (MACES) pressure suit and helmet, and driven with loadings similar to what is expected for the actual Orion vehicle during landing, launch abort, and chute deployment. Test data will be compared to analytical predictions and modelling uncertainty factors will be determined for each injury metric. Additionally, the test data will be used to further improve the FE model, particularly in the areas of the ATD neck components, harness, and suit and helmet effects.

Lawrence, C.↗
NASA NTRS2002

A Data-Driven Solution for Performance Improvement

Marketed as the "Software of the Future," Optimal Engineering Systems P.I. EXPERT(TM) technology offers statistical process control and optimization techniques that are critical to businesses looking to restructure or accelerate operations in order to gain a competitive edge. Kennedy Space Center granted Optimal Engineering Systems the funding and aid necessary to develop a prototype of the process monitoring and improvement software. Completion of this prototype demonstrated that it was possible to integrate traditional statistical quality assurance tools with robust optimization techniques in a user- friendly format that is visually compelling. Using an expert system knowledge base, the software allows the user to determine objectives, capture constraints and out-of-control processes, predict results, and compute optimal process settings.

Source record↗
DOE OSTI2021

Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing

The geometric flexibility of additively manufactured metals and ceramics generates a very large and open design space that requires advanced modeling and simulation tools for physics simulations and the rigorous definition of design problems. This effort deploys artificial intelligence (AI) and machine learning (ML) algorithms to understand the design space, evaluate potential designs, and more efficiently generate optimized results. The Transformational Challenge Reactor (TCR) program is leveraging advances in several scientific areas—including materials, manufacturing, sensors and control systems, data analytics, and high-fidelity modeling and simulation—to accelerate the design, manufacturing, qualification, and deployment of advanced nuclear energy systems. Through a manufacturing-informed design approach, the TCR program seeks to integrate digital data for rapid nuclear innovation; accelerate the adoption of advances in manufacturing, materials, and computational sciences for nuclear applications; and dramatically reduce deployment costs and timelines for new nuclear reactor technologies. This report documents efforts under the TCR program to leverage advanced modeling and simulation techniques driven by AI/ML algorithms on high-performance computing (HPC) systems to yield more optimized TCR core designs. A multiphysics ML surrogate model was developed to run on the HPC architectures. The surrogate model is trained on high-fidelity simulation data of coupled neutronics and thermofluidics and is used to quickly evaluate thousands of candidate core designs in parallel, which drives the evolution of the cooling channel shapes to minimize temperature peaking and material stress. Outcomes from these activities provide design information and feedback into the core design efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Diagnosing the DARHT Electron Beam-Target Interaction and Hydrodynamic Expansion [Dissertation]

Quantitative electron beam-target interaction studies on the Dual-Axis Radiographic Hydrodynamic Test (DARHT) electron linear induction accelerators have only been performed recently. This includes characterization of the temperature, density, pressure, extent, and expansion velocity of the plasma plume. The results presented in this dissertation present a detailed and unified overview of the accelerator systems, target heating physics, beam transport, and diagnostic tools. Additional information includes calibration sources, radiation hydrodynamics, spectroscopic-quality radiation transport modeling, experimental measurements, and analyses of electron beam driven aluminum experiments. The first set of spatially and temporally resolved spectroscopic measurements of electron beam driven aluminum are presented. Contamination quantification analyses are used to understand the origin of the strong Na-I 3p-3s lines that are observed in absorption within the aluminum plasma continuum. These results inform the creation of the first spectroscopic-quality radiation transport model that links several atomic physics codes to interpret the conditions from which the Na-I lines originate. A good agreement is found between the surface analysis results and the model which confirms the concentration of the sodium present within the aluminum alloy foil material. It also demonstrates, for the first time on electron beam-driven target experiments, the ability to interpret plasma conditions from measured absorption lines. In a second experimental campaign which focuses on pure aluminum, the Al-I 3p-4s and 3p3d doublets are both measured in emission. A detailed analysis of the Al-I 3p-4s doublet reveals that the lines undergo moderate self-absorption. A simple model of the self-absorption effect is successfully used to match measured spectra at various temperature/density/plasma scale length combinations. These measurements led to the realization of the minimum density that can be resolved by the spectrometers for the Al-I 3p-4s lines due to the large slit width required to observe a signal on aluminum. These measurements also demonstrate the sensitivity of visible and long wave UV spectroscopy to minor changes in both temperature and density. The simple self-absorption model will be useful for analysis of other beam-target interaction experiments with spectra exhibiting either self-absorption or full self-reversal. Substantial headway has been made on the modeling front by linking together several codes needed to model both the energy deposition, hydrodynamic motion, and atomic kinetics to produce synthetic spectral calculations that are compared with experimental measurements. There exists ample space for improvement, especially with benchmarking the hydrodynamics codes and equation-of-state tables with experimental measurements. The X-ray diagnostics required to make these new measurements along with the simulation capabilities required to interpret the results are under development and will be the subject of future studies.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

A plasma deflagration accelerator as a platform for laboratory astrophysics

The replication of astrophysical flows in the laboratory is critical for isolating particular phenomena and dynamics that appear in complex, highly-coupled natural systems. Particularly, plasma jets are observed in astrophysical contexts at a variety of scales, typically at high magnetic Reynolds number and driven by internal currents. In this paper, we present detailed measurements of the plasma parameters within deflagration-produced plasma jets, the scaling of these parameters against both machine operating conditions and the corresponding astrophysical phenomena. Using optical and spectroscopic diagnostics, including Schlieren cinematography, we demonstrate the production of current-driven plasma jets of »100 km/s and magnetic Reynolds numbers of »100, and discuss the dynamics of their acceleration into vacuum. Finally, the results of this study will contribute to the reproduction of various types of astrophysical jets in the laboratory and indicate the ability to further probe active research areas such as jet collimation, stability, and interaction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Lessons Learned from Open-Source Software Training Toward Expanding the Fusion Workforce

Within the United States (U.S.), the Fusion Innovation Research Engine (FIRE) Collaboratives seek to accelerate fusion technology development through wide-ranging community-driven research activities that bring together industry, laboratories, research institutes, and academia. Increasing the maturity of key components and systems for future fusion power plants (FPPs) toward commercialization, will, by necessity, increase the need for knowledgeable engineers, designers, and researchers in industry capable of integrating and further improving these technologies within industry FPP concepts. Further, various modeling and simulation packages support these programs and are under-development within them to drive design iteration and the development of FPP digital twins. To derive the greatest benefit from model output and capabilities, training these same specialists will be vital. Thus, the development of effective and accessible software onboarding and professional development opportunities focused on fusion will be key to keeping the pace of growth high in the coming decade and beyond. A similar need exists within the advanced fission reactor community, driven by an ever-growing need for carbon-free baseload power for industrial and data center applications. Within the U.S. and around the world, several open-source packages and frameworks exist to support this endeavor, and two we will highlight here are the Multiphysics Object Oriented Simulation Environment (MOOSE) framework and OpenMC. These packages, notably, are also being utilized in the FIRE Collaboratives program. In this presentation, we will highlight the lessons learned from over 30 years of combined software development and training experience, focused on developing strong technical software foundations within the nuclear workforce, from students to professional engineers & scientists. We will connect this experience to present and emerging needs in the fusion energy community, and, finally, will outline possible paths forward to develop a large, robust, global fusion workforce.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

The Role of Topography in Controlling Evapotranspiration Age

Abstract Evapotranspiration (ET) age is a key metric of water sustainability but a major unknown partly due to the extreme difficulty in modeling it. Groundwater is found to be important in ET age variations in small‐scale studies, yet our understanding is insufficient because groundwater systems are nested across scales. Here, we conducted GPU‐accelerated particle tracking with integrated hydrologic modeling to quantify the variations in ET age at a regional scale of ∼0.4 M km 2 . Simulation results reveal topography‐driven flow paths shaping the spatial and temporal patterns of ET age variations. On ridges, where root zone decoupling with deep subsurface storage, ET age is generally young, with seasonal variations dominated by meteorological conditions. In the valley bottom, ET age is generally old, with significant subseasonal variations caused by the convergence of subsurface flow paths. On hillslopes with water table depths ranging from 1 to 10 m, ET age shows strong seasonal variations caused by the connections with lateral groundwater regulated by ET demand. Our modeling approach provides insights into the basic linkages between ET age and topography at large scale. Our work highlights the perspective of multiscale studies of ET age, suggesting new field experiments to test these process connections and to determine if such linkages warrant inclusion in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

An ultrashort pulse ultra-violet radiation undulator source driven by a laser plasma wakefield accelerator

Narrow band undulator radiation tuneable over the wavelength range of 150–260 nm has been produced by short electron bunches from a 2 mm long laser plasma wakefield accelerator based on a 20 TW femtosecond laser system. The number of photons measured is up to 9 × 10{sup 6} per shot for a 100 period undulator, with a mean peak brilliance of 1 × 10{sup 18} photons/s/mrad{sup 2}/mm{sup 2}/0.1% bandwidth. Simulations estimate that the driving electron bunch r.m.s. duration is as short as 3 fs when the electron beam has energy of 120–130 MeV with the radiation pulse duration in the range of 50–100 fs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Numerical eigen-spectrum slicing, accurate orthogonal eigen-basis, and mixed-precision eigenvalue refinement using OpenMP data-dependent tasks and accelerator offload

Performing a variety of numerical computations efficiently and, at the same time, in a portable fashion requires both an overarching design followed by a number of implementation strategies. All of these are exemplified below as we present transitioning the PLASMA numerical library from relying on dependence-driven large tasks to achieving utilization of fine grain tasking and offload to hardware accelerators while keeping its core dependence sets: OpenMP source code pragmas and runtime for most system-level functionality and basic low-level numerical kernels provided directly by hardware vendors or open source projects with vendor contributions. We also present new algorithmic methods and their efficient parallel implementations including fine grained tasking for eigen-spectrum slicing and offload for mixed-precision eigenvalue refinement. We provide performance, scaling, and numerical results showing sizable gains over the available solutions from either the open source and vendor-provided packages.

Luszczek, Piotr↗
DOE OSTI2025

Multi-Beam-Energy Control Unit Based on Triple-Bend Achromats

X-ray free electron lasers (XFELs) are the new generation of particle accelerator-based light sources, capable of producing tunable, high-power X-ray pulses that are increasingly vital across various scientific disciplines. Recently, continuous-wave (CW) XFELs driven by superconducting linear accelerators have garnered significant attention due to their ability to enhance availability by supporting multiple undulator lines simultaneously. In this paper, we introduce a novel delay system comprising four triple-bend achromats (TBAs). This delay system was combined with fast kickers and can be employed to generate electron beams on a bunch-to-bunch basis in a CW-XFEL facility. Based on the parameters of the Shanghai High-Repetition-Rate XFEL and Extreme Light Facility, start-to-end simulations demonstrate that the TBA-based delay system achieves excellent electron beam qualities while providing a wide beam-energy-tuning range from 1.39 to 8 GeV.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Accelerated optimization of pure metal and ligand compositions for light-driven hydrogen production

Photocatalytic hydrogen production is a promising alternative to traditional hydrogen production. To implement photocatalytic hydrogen production the development of efficient, sustainable, and stable catalysts is necessary, and overcoming the current challenges surrounding high dimensional search spaces requires both computational and experimental efforts. Utilizing photo driven processes, stable colloidal metal catalysts can be formed in situ for efficient hydrogen production from water. When considering colloidal catalysts, stability is typically a concern solved through the addition of supports or ligands. In this work, poly(ethylene glycol) methyl ether thiol acts as a stabilizing ligand eliminating the need for catalyst supports while providing stable and active nanoparticle catalysts for more than 45 hours of reaction time and illumination. These systems utilize molecular photosensitizers, water reduction catalysts, stabilizing ligands, water, a sacrificial reductant, and organic solvents, posing new challenges pertaining to the optimization of multi-variable systems. Design of experiments (DOE) is applied to accelerate the understanding of variable interactions and is used as a tool to rapidly optimize the compositions of Au, Cu, Ni, and Fe containing systems. Through a collaboration leveraging computation and experimentation (both high throughput and characterizations), optimized performance peaks were obtained for each of these metals alongside distinct mapping of expected activity associated with photosensitizer, metal, and ligand concentration variations. With the highly digitized workflow, this study allowed for comparative generalizations to be made regarding photo driven hydrogen production for all four metals.

08 HYDROGEN↗
DOE OSTI2014

ADVANTG Results for a Proposed NDA System for Detecting Pin Diversion from SNF - Paper 120

This summary describes the results of applying the ADVANTG variance reduction parameter generator to accelerate continuous-energy Monte Carlo simulations of the {sup 252}Cf Interrogation with Prompt Neutron (CIPN) detection system proposed by Hu et al. for detecting the diversion of fuel elements from spent nuclear fuel (SNF) assemblies. In previous work, ADVANTG was applied to a suite of nine radiation detection, special nuclear material (SNM) movement detection, and safeguards test cases. That effort demonstrated that ADVANTG was able to provide large increases in tally figures of merit (FOMs) in nearly all of the cases without introducing bias into the Monte Carlo results. The objective of the work described here is to further evaluate ADVANTG, and also to identify gaps in capability with regard to nuclear safeguards applications, by applying the code to a challenging problem that is of a different nature from the ones previously studied. The CIPN nondestructive assay (NDA) system consists of three fission chambers embedded in a C-shaped block of polyethylene and a polyethylene-moderated {sup 252}Cf source that are placed on opposite sides of a subject SNF assembly. The idea of the detection system is to measure the difference between the background neutron count rate, due to spontaneous fission in the fuel material, and the count rate observed once the source is introduced, which is dominated by multiplication within the assembly. Based on the difference between these count rates, the fissile content of the assembly can be inferred, and this information can be used to determine if some fraction of the original fuel pins have been replaced with depleted uranium substitutes. The authors report that the system can detect the replacement of at least eight pins (3% of total mass). The ADVANTG code generates space- and energy-dependent weight-window bounds and biased source distributions based on approximate transport solutions that are efficiently generated by the Denovo 3-D discrete ordinates package. ADVANTG implements the Consistent Adjoint Driven Importance Sampling (CADIS) method for accelerating individual tallies and the Forward-Weighted CADIS (FW-CADIS) method for obtaining relatively uniform uncertainties across tallies over multiple regions and/or energy bins. The variance reduction parameters are generated in a format directly usable by standard versions of MCNP5 and MCNPX. In this work, the ADVANTG variance reduction parameter generator was applied to accelerate continuous energy MCNPX simulations of the {sup 252}Cf Interrogation with Prompt Neutron detection system for detecting the diversion of fuel elements from SNF assemblies. Variance reduction parameters generated with the existing version of ADVANTG actually slowed down tally convergence in all cases. The cause of the poor performance was found to be the lack of an induced fission source treatment in the fixed-source discrete ordinates calculations employed by ADVANTG. Because fission was treated as capture and not as a source, the importance maps generated by ADVANTG significantly underestimated the importance of thermal neutrons in and around the fuel elements. In order to obtain improved results, we developed an experimental implementation of a fission source outer iteration for the adjoint calculations. We used this prototype capability to generate new variance reduction parameters and found that the mean fission rates agreed well with those predicted by the conventional MCNPX simulations, as was expected. With these new parameters, speedup factors of 59 to 80 were obtained for the case with the background source, and factors of 17 to 24 were obtained for the cases with the interrogating source. These results demonstrate that a fission source treatment is needed to improve the effectiveness of ADVANTG in problems where the effects of induced fission are important. This includes many types of NDA problems that are relevant to safeguards applications. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Molten salt considerations for accelerator-driven subcritical fission to close the nuclear fuel cycle

The host salt selection, molecular modeling, physical chemistry, and processing chemistry are presented here for an accelerator-driven subcritical fission in a molten salt core (ADSMS). The core is fueled solely with the transuranics (TRU) and long-lived fission products (LFP) from used nuclear fuel. The neutronics and salt composition are optimized to destroy the transuranics by fission and the long-lived fission products by transmutation. The cores are driven by proton beams from a strong-focusing cyclotron stack. One such ADSMS system can destroy the transuranics in the used nuclear fuel produced by a 1GWe conventional reactor. It uniquely provides a method to close the nuclear fuel cycle for green nuclear energy.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Applications of compact accelerator-driven neutron sources: An updated assessment from the perspective of materials research in Italy

In 2005 the International Atomic Energy Agency (IAEA) in Vienna published a report [1] on ‘Development Opportunities of Small and Medium Scale Accelerator Driven Neutron Sources’ which summarized the prospect of smaller sources in supporting the large spallation neutron sources for materials characterization and instrumentation, a theme advocated by Bauer, Clausen, Mank, and Mulhauser in previous publications [2-4]. In 2010 the Union for Compact Accelerator-driven Neutron Sources (UCANS) was established [5], galvanizing cross-disciplinary collaborations on new source and neutronics development and expanded applications based on both slow-neutron scattering and other neutron-matter interactions of neutron energies ranging from 10⁻⁶ to 10² MeV [6]. Here, we first cover the recent development of ongoing and prospective projects of compact accelerator-driven neutron sources (CANS) but concentrate on prospective accelerators currently proposed in Italy. Two active R&D topics, irradiation effects on electronics and cultural heritage studies, are chosen to illustrate the impact of state-of-the-art CANS on these programs with respect to the characteristics and complementarity of the accelerator and neutronics systems as well as instrumentation development.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Photodegradation accelerates ecosystem N cycling in a simulated California grassland

Abstract Photodegradation accelerates litter decay in arid grasslands where plant growth and litter decay are strongly controlled by precipitation and evapotranspiration. However, the effects of photodegradation on ecosystem C and N dynamics are not well understood. We examined the effects using an ecosystem biogeochemical model DayCent‐ UV with photodegradation explicitly represented and validated. The model was parameterized for a California grassland where photodegradation was documented to release CO 2 from litter. The model was parameterized with an inverse modeling approach using an extensive data set of six years of daily observed carbon and water gas exchange (gross primary production, ecosystem respiration, and evapotranspiration), soil temperature, and soil moisture. DayCent‐ UV correctly simulated the seasonal patterns of the observed gas exchange and closely simulated the inter‐annual variation in the gas exchange and biomass production rates. The simulations suggested that the inter‐annual variation is driven more by actual evapotranspiration than by precipitation because a large portion of precipitation is lost as runoff during wet years. Photodegradation in DayCent‐ UV accelerated C and N cycling, decreasing system C and N by 9.2% and 9.5% and C and N residence times by 9.4% and 18.2%. Accelerated N cycling made a greater fraction of system N available for plants, increasing net N mineralization and plant production for a given amount of system N. Increased net N mineralization was due to decreased immobilization by microbes in the aboveground organic matter. Photodegradation did not alter the control on plant production by evapotranspiration. These results suggest that at the ecosystem level, the central effect of photodegradation is to suppress microbial activity. We conclude that photodegradation accelerates N cycling at the expense of microbes in this grassland, making it more efficient in supporting plant growth for a given amount of N in the system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.

97 MATHEMATICS AND COMPUTING↗