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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 1,189 records · Page 66

A Scoping Study to Develop a Computational Fluid Dynamics Based Model to Predict Radiological Materials Packaging Temperatures within a Generic Staging Building

The objective of this work is to perform computational fluid dynamics simulations of a ventilated radiological-material-package staging building to determine the effect of including or excluding a variety of physical effects and computational methods on both the predicted package temperatures and required computational resources. The generic building contains 640 drum-packages containing heat-generating, radiological material supported on four racks that are eight levels tall. Additionally, there is a forced ventilation system, lighting, and insulated walls. Computational models were constructed that included or excluded (a) shelving, (b) effects of unsteadiness, and (c) radiation heat transfer. Simulations with each drum modeled separately were compared to simpler simulations with sets of four drums represented by an equivalent box-package. These models employed between 106 to 107 elements. Steady state simulations predicted package temperatures that were within 0.1°C of simulations that included transient effects and required only one-eighth the computational resources. Calculations that excluded shelving predicted temperatures within 0.6°C of simulations that included shelving and required one-fourth the computational resources. Excluding radiation heat transfer systematically increased temperatures by around 1.5°C but reduced computational resources by a factor of four. The box-package model reduced the computational resources by a factor of 3, but systematically predicted higher temperatures by around 1.1°C. These results will be used to develop an efficient computational fluid dynamics model to assess the ability of different staging building designs to prevent the temperature of package components from exceeding specified limits.

42 ENGINEERING↗

Some statistical performance characteristics of the 'ITD' modal identification algorithm

Performance characteristics of the Ibrahim time-domain algorithms are examined on a statistical basis. The method uses multiple free-response measurements from a test structure directly in the time domain, and displays varying accuracy, with the strongly excited modes identified most accurately and the weakly excited modes least accurately. Sets of computer-generated free-response functions for a simple 1-mode model are used to study the identification performance for several basic changes in the modal characteristics of the data, the user-selectable analysis constants, and the level of superimposed noise. Results indicate the existence of a direct and often linear effect of noise on the scatter of identified parameters, and good identification is maintained at the 1% noise level down to the point in frequency when only 1/4-cycle of data is analyzed.

Pappa, R. S.↗

Eigenvalue assignment strategies in rotor systems

The work done to establish the control and direction of effective eigenvalue excursions of lightly damped, speed dependent rotor systems using passive control is discussed. Both second order and sixth order bi-axis, quasi-linear, speed dependent generic models were investigated. In every case a single, bi-directional control bearing was used in a passive feedback stabilization loop to resist modal destabilization above the rotor critical speed. Assuming incomplete state measurement, sub-optimal control strategies were used to define the preferred location of the control bearing, the most effective measurement locations, and the best set of control gains to extend the speed range of stable operation. Speed dependent control gains were found by Powell's method to maximize the minimum modal damping ratio for the speed dependent linear model. An increase of 300 percent in stable speed operation was obtained for the sixth order linear system using passive control. Simulations were run to examine the effectiveness of the linear control law on nonlinear rotor models with bearing deadband. The maximum level of control effort (force) required by the control bearing to stabilize the rotor at speeds above the critical was determined for the models with bearing deadband.

Youngblood, J. N.↗

Mars Radiator Characterization Experimental Program

Radiators are an enabling technology for the human exploration and development of the moon and Mars. As standard components of the heat rejection subsystem of space vehicles, radiators are used to reject waste heat to space and/or a planetary environment. They are typically large components of the thermal control system for a space vehicle or human habitation facility, and in some cases safety factors are used to oversize them when the operating environment cannot be fully characterized. Over-sizing can impose significant weight and size penalties that might be prohibitive for future missions. Radiator performance depends on the size of the radiator surface, its emittance and absorptance, the radiator temperature, the effective sky temperature surrounding the radiator, solar radiation and atmospheric irradiation levels, convection to or from the atmosphere (on Mars), and other conditions that could affect the nature of the radiator surface, such as dust accumulation. Most particularly, dust is expected to be a major contributor to the local environmental conditions on either the lunar or Martian surface. This conclusion regarding Mars is supported by measurements of dust accumulation on the Mars Sojourner Rover solar array during the Pathfinder mission. This Final Report describes a study of the effect of Martian dust accumulation on radiator performance. It is comprised of quantitative measurements of effective emittance for a range of dust accumulation levels on surfaces of known emittance under clean conditions. The test radiator coatings were Z-93P, NS-43G, and Silver Teflon (10 mil) film. The Martian dust simulant was Carbondale Red Clay. Results were obtained under vacuum conditions sufficient to reduce convection effects virtually to zero. The experiments required the development of a calorimetric apparatus that allows simultaneous measurements of the effective emittance for all the coatings at each set of experimental conditions. A method of adding dust to multiple radiator coupons was developed and shown to be capable of depositing dust on the surfaces with acceptable uniformity. In these experiments, the dust layer accumulates under earth gravity and in the presence of an earth atmosphere. An invention disclosure for the dust deposition apparatus is being filed through NASA and University of Houston.

Witte, Larry C.↗

Leak Rate Quantification Method for Gas Pressure Seals with Controlled Pressure Differential

An enhancement to the pressure decay leak rate method with mass point analysis solved deficiencies in the standard method. By adding a control system, a constant gas pressure differential across the test article was maintained. As a result, the desired pressure condition was met at the onset of the test, and the mass leak rate and measurement uncertainty were computed in real-time. The data acquisition and control system were programmed to automatically stop when specified criteria were met. Typically, the test was stopped when a specified level of measurement uncertainty was attained. Using silicone O-ring test articles, the new method was compared with the standard method that permitted the downstream pressure to be non-constant atmospheric pressure. The two methods recorded comparable leak rates, but the new method recorded leak rates with significantly lower measurement uncertainty, statistical variance, and test duration. Utilizing this new method in leak rate quantification, projects will reduce cost and schedule, improve test results, and ease interpretation between data sets.

seal↗

Advanced Background Subtraction Applied to Aeroacoustic Wind Tunnel Testing

An advanced form of background subtraction is presented and applied to aeroacoustic wind tunnel data. A variant of this method has seen use in other fields such as climatology and medical imaging. The technique, based on an eigenvalue decomposition of the background noise cross-spectral matrix, is robust against situations where isolated background auto-spectral levels are measured to be higher than levels of combined source and background signals. It also provides an alternate estimate of the cross-spectrum, which previously might have poor definition for low signal-to-noise ratio measurements. Simulated results indicate similar performance to conventional background subtraction when the subtracted spectra are weaker than the true contaminating background levels. Superior performance is observed when the subtracted spectra are stronger than the true contaminating background levels. Experimental results show limited success in recovering signal behavior for data where conventional background subtraction fails. They also demonstrate the new subtraction technique's ability to maintain a proper coherence relationship in the modified cross-spectral matrix. Beam-forming and de-convolution results indicate the method can successfully separate sources. Results also show a reduced need for the use of diagonal removal in phased array processing, at least for the limited data sets considered.

Bahr, Christopher J.↗

MY EXES and EDM for Automated Remediation Data Quality Assessments - 19053

MY Electronic data exchange and Evaluation System (EXES) is a new web-based technology providing external admin access and full control to the Web-based EXES tool developed by GD for EPA for automated environmental remediation data quality assessments. EXES replaces most manual assessment processes, reducing remediation data review time and costs and ensuring that data are of known and documented quality. This tool is available from EPA to federal agencies and remediation firms and has successfully been used to support over 190 site investigations, 105 Remedial investigations and over 20 compliance monitoring efforts. The new MY EXES functionality has been developed for project managers and decision makers to setup projects, track receipt of environmental remediation monitoring data, assess data quality, and manage data. It is designed to be flexible and configurable to meet any government agency's data review and data management needs. It is accessible 24/7 through a secure portal. MY EXES efficiently evaluates analytical data regardless of the underlying method and data reporting requirements. It is a centralized project and data assessment tool that is scalable, flexible and configurable; improving data quality while reducing cost through the following: - Provides users with the ability to create a project and to specify the analytical methods corresponding to the data that will be submitted for that project. A project can be modified and managed anytime during the project's life cycle. - Allows users to manage a library of analytical methods that can be made available for association to their projects. - Users can specify the automated tests and assessment that needs to be performed on the analytical data deliverables based on specific requirements in the project's Quality Assurance Project Plan (QAPP). - Users specify: - The format of the incoming data deliverables from the laboratory; - The type and level of review services to be performed; - The assessment deliverables to be generated - output spreadsheets and reports; - Project owner sets up system access and permissions for members of the project team. - A faster (600%) and less expensive (85%) process than the traditional data usability/validation. The EXES Data Manager application (EDM) provides a centralized data repository to view and retrieve generated reports, spreadsheets, and other data deliverables as defined by the client, eliminating the need for data transfer between project team members. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Preliminary structural assessment of VHTR graphite components according to ASME code - 18532

In this study, a preliminary structural assessment on a graphite component of a VHTR was done in accordance with the semi-probabilistic assessment procedures of the latest 2015 edition of the ASME Boiler and Pressure Vessel Code, Section III, Div. 5, Subpart HHA-Graphite Materials. Establishment of the Weibull distribution for the tensile strength is essential to set up the stress limits based on the probability of failure of the graphite materials. All parameters required in the ASME code were identified and evaluated for a nuclear graphite material, IG-110. The assessment of design level was done on one of fuel elements in a Korean VHTR design by two methodologies in the ASME code: (1) Simplified assessment and (2) Full assessment. The structural integrity of the fuel element was assured by both assessment methods. Also, the effect of the number of integration volume groups on the probability of failure in the full assessment was investigated and a recommendation for the conservative results was suggested. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Prioritizing Nuclear Materials for SAM-3 Neutron Irradiation Campaign: Structural and Cladding Materials Candidates

This report outlines a framework for selecting structural and cladding materials for the Nuclear Science User Facilities (NSUF) SAM-3 neutron irradiation campaign to support the advancement of nuclear energy technologies. The document begins with an introduction that provides background context, highlights the motivations for launching a new irradiation campaign, and defines the overall objectives. The core of the report describes the design considerations for the irradiation campaign, including capsule configurations, irradiation temperature ranges, and target dose levels (defined by displacements per atom, or dpa). The material recommendation was guided by the Specimen Identification and Prioritization (SIP) Working Group, a multidisciplinary team of experts representing national laboratories, academia, industry, federal government and agency. This group played a central role in identifying candidate materials, evaluating technical justifications, and ensuring alignment with boarder programmatic goals. A detailed set of criteria for material prioritization is then presented, taking into account reactor relevance, performance gaps, advanced manufacturing methods, and emerging material classes. Based on the input of SIP working group, specific materials were selected and justified for inclusion in the irradiation campaign by the NSUF leadership and its U.S. Department of Energy (DOE)-Office of Nuclear Energy (NE) management. The final section provides recommended capsule designs, summarizing critical parameters such as material type, fabrication method, sample geometry, irradiation conditions, and specimen quantities. This report serves as a foundation for executing a focused and high-impact neutron irradiation campaign aimed at addressing key materials challenges for both existing and advanced nuclear reactors.

36 - MATERIALS SCIENCE↗

Investigation of Plasmodium falciparum pfhrp2 and pfhrp3 gene deletions and performance of a rapid diagnostic test for identifying asymptomatic malaria infection in northern Ethiopia, 2015

Background: Rapid diagnostic tests (RDTs) are widely used for malaria diagnosis of both symptomatic and asymptomatic infections. Although RDTs are a reliable and practical diagnostic tool, the sensitivity of histidine-rich protein 2 (HRP2)-based RDTs can be reduced if pfhrp2 or pfhrp3 (pfhrp2/3) gene deletions exist in the Plasmodium falciparum parasite population. This study evaluated dried blood spot (DBS) samples collected from a national household survey to investigate the presence of pfhrp2/3 deletions and the performance of the RDT used in the cross-sectional survey in a low transmission setting. Methods: The 2015 Ethiopia Malaria Indicator Survey tested household members by RDT and collected DBS samples. DBS (n = 2648) from three regions in northern Ethiopia were tested by multiplex bead-based antigen detection assay after completion of the survey. The multiplex assay detected pan-Plasmodium lactate dehydrogenase (LDH), pAldolase, and HRP2 antigens in samples. Samples suspected for pfhrp2/3 gene deletions (pLDH and/or pAldolase positive but low or absent HRP2) were further investigated by molecular assays for gene deletions. Antigen results were also compared to each individual’s RDT results. Dose–response logistic regression models were fit to estimate RDT level of detection (LOD) antigen concentrations at which 50, 75, 90, and 95% of the RDTs returned a positive result during this survey. Results: Out of 2,648 samples assayed, 29 were positive for pLDH or pAldolase antigens but low or absent for HRP2 signal, and 15 of these samples (51.7%) were successfully genotyped for pfhrp2/3. Of these 15 P. falciparum infections, eight showed single deletions in pfhrp3, one showed a single pfhrp2 deletion, and six were pfhrp2/3 double-deletions. Six pfhrp2 deletions were observed in Tigray and one in Amhara. Twenty-five were positive for HRP2 by the survey RDT while the more sensitive bead assay detected 30 HRP2-positive samples. A lower concentration of HRP2 antigen generated a positive test result by RDT compared to pLDH (95% LOD: 16.9 ng/mL vs. 319.2 ng/mL, respectively). Conclusions: There is evidence of dual pfhrp2/3 gene deletions in the Tigray and Amhara regions of Ethiopia in 2015. As the prevalence of malaria was very low (< 2%), it is difficult to make strong conclusions on RDT performance, but these results challenge the utility of biomarkers in household surveys in very low transmission settings.

60 APPLIED LIFE SCIENCES↗

Preparation for Pick-and-Eat Food Production on the International Space Station: Flight Definition for the VEG-04 and VEG-05 Missions

Growth of fresh, nutritious, palatable produce for crew consumption during spaceflight may provide health-promoting, bioavailable nutrients and enhance the dietary experience as we move toward longer-duration missions. Tending plants also may serve as a countermeasure for crew psychological stresses associated with long duration spaceflight. However, requirements to support consistent growth of a variety of high quality, nutritious crops under spaceflight environmental conditions is unknown. This study is exploring the potential to grow plants for food production on the International Space Station (ISS) using the Veggie vegetable production system. Ground testing is underway to compare the impacts of several fertilizer and lighting treatments on growth, quality, and nutritional composition of the leafy green crop mizuna, and the dwarf tomato crop Red Robin when subjected to Veggie ISS environmental conditions. Early testing focused on the leafy crop Tokyo Bekana Chinese cabbage, but ground tests indicated that this plant suffered from stress responses when grown under LEDs and the chronically elevated CO2 levels found on the ISS. Mizuna, a related leafy variety that grows well in the presence of high CO2, and has excellent organoleptic characteristics, was selected as an alternate crop. Tomato crops have been grown using two fertilizer formulations and two pollination techniques, and growth tests using different red:blue lighting environments are underway. Chemical analysis is also being conducted and these data, when coupled with the growth results, will be used to down-select to the two best lighting treatments and best fertilizer treatment for future testing of each crop on the ISS. Additionally, seed-source testing has become important, with mizuna seeds from two different vendors growing very differently. A seed source has been selected, and seed-surface-sanitizing methods have been confirmed for mizuna, but these remain under development for tomato. A crop-handling protocol is also being evaluated to support food safety. All harvests reserve a subset of samples for microbial analysis to determine baseline microbial levels and help establish critical control points for food safety. Testing was initially conducted in hardware analogs of the standard Veggie plant pillows. However, a new Veggie watering system, the Passive Orbital Nutrient Delivery System or PONDS, has been designed and is being prepared for future flight experiments. With the selection of this growth system, ground tests have shifted to analog PONDS systems. Crop tests on ISS, designated VEG-04 for mizuna and VEG-05 for tomato, are planned in 2018 to evaluate any additional impacts of spaceflight on the light and fertilizer conditions down-selected from ground tests. A set of Veggie-specific questions has been developed to characterize the psychological impacts of plant growth and plant-care activities during spaceflight. Organoleptic questionnaires have been developed to assess produce attributes in microgravity taste sessions. These tests for plants growing in the Veggie hardware on ISS will help to mitigate the risk of an inadequate food supply for long duration missions by developing methods and determining hardware requirements to integrate fresh vegetables as a dietary supplement. This research was co-funded by the Human Research Program and Space Biology (MTL1075) in the ILSRA 2015 NRA call.

Veggie↗

Preparation for Pick-and-Eat Food Production on the International Space Station: Flight Definition for the VEG-04 and VEG-05 Missions

Growth of fresh, nutritious, palatable produce for crew consumption during spaceflight may provide health-promoting, bioavailable nutrients and enhance the dietary experience as we move toward longer-duration missions. Tending plants also may serve as a countermeasure for crew psychological stresses associated with long duration spaceflight. However, requirements to support consistent growth of a variety of high quality, nutritious crops under spaceflight environmental conditions is unknown. This study is exploring the potential to grow plants for food production on the International Space Station (ISS) using the Veggie vegetable production system. Ground testing is underway to compare the impacts of several fertilizer and lighting treatments on growth, quality, and nutritional composition of the leafy green crop mizuna, and the dwarf tomato crop "Red Robin" when subjected to Veggie ISS environmental conditions. Early testing focused on the leafy crop "Tokyo Bekana" Chinese cabbage, but ground tests indicated that this plant suffered from stress responses when grown under LEDs and the chronically elevated CO2 levels found on the ISS. Mizuna, a related leafy variety that grows well in the presence of high CO2, and has excellent organoleptic characteristics, was selected as an alternate crop. Tomato crops have been grown using two fertilizer formulations and two pollination techniques, and growth tests using different red:blue lighting environments are underway. Chemical analysis is also being conducted and these data, when coupled with the growth results, will be used to down-select to the two best lighting treatments and best fertilizer treatment for future testing of each crop on the ISS. Additionally, seed-source testing has become important, with mizuna seeds from two different vendors growing very differently. A seed source has been selected, and seed-surface-sanitizing methods have been confirmed for mizuna, but these remain under development for tomato. A crop-handling protocol is also being evaluated to support food safety. All harvests reserve a subset of samples for microbial analysis to determine baseline microbial levels and help establish critical control points for food safety. Testing was initially conducted in hardware analogs of the standard Veggie plant pillows. However, a new Veggie watering system, the Passive Orbital Nutrient Delivery System or PONDS, has been designed and is being prepared for future flight experiments. With the selection of this growth system, ground tests have shifted to analog PONDS systems. Crop tests on ISS, designated VEG-04 for mizuna and VEG-05 for tomato, are planned in 2018 to evaluate any additional impacts of spaceflight on the light and fertilizer conditions down-selected from ground tests. A set of Veggie-specific questions has been developed to characterize the psychological impacts of plant growth and plant-care activities during spaceflight. Organoleptic questionnaires have been developed to assess produce attributes in microgravity taste sessions. These tests for plants growing in the Veggie hardware on ISS will help to mitigate the risk of an inadequate food supply for long duration missions by developing methods and determining hardware requirements to integrate fresh vegetables as a dietary supplement. This research was co-funded by the Human Research Program and Space Biology (MTL#1075) in the ILSRA 2015 NRA call.

LED light↗

TROPoe retrievals from SGP C1

The TROPoe (formerly called AERIoe) algorithm (Turner and L&ouml;hnert 2014, 2021; Turner and Blumberg 2019) retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum. The data can be used to characterize the evolution of the planetary boundary layer and boundary layer clouds. This data set was collected at the ARM SGP Central Facility (CF) during and after the MicroPulse DIAL Demonstration (MPDDEMO) field campaign. The TROPoe retrieval was run at 5-minute resolution, but retrievals can be performed at the maximum temporal resolution of the AERI instrument (order 30 s) -- if this higher temporal resolution is desired, please contact Dave Turner. This is a physical-iterative retrieval method. The retrieval of thermodynamic profiles from spectral infrared radiance observations is an ill-posed problem, and thus constraints need to be included in the retrieval algorithm to provide physically plausible results. Here, we use a climatology of radiosonde profiles collected at the ARM SGP site during the summer as our prior information in an optimal estimation framework. Surface meteorology and output from the rapid-refresh (RAP) numerical weather prediction model (above 4 km) were used as additional constraints by the retrieval. As the method uses an optimal estimation framework, a full error covariance matrix of each solution is included in the output file. The 1-sigma uncertainty of each retrieved variable, which is derived from the error covariance matrix, is included for each scientific field and is named "sigma_X", where "X" is the name of the scientific field (e.g., 'temperature'). The information content in the AERI observations, which is in the "dfs" field, on the thermodynamic profiles is primarily concentrated in the lowest 3 km or up to cloud base; the retrieved data should not be used above that level (or used with caution). There is an overall "qc_flag" field that is set when a retrieval should not be trusted. However, the logic that sets this flag did not work correctly, and it should not be used. Instead, consider all retrievals that have a value for "converged_flag" greater than 0 as valid. If you have any questions, contact Dave Turner. This is Release_2_12 of the TROPoe algorithm.

54 ENVIRONMENTAL SCIENCES↗

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗

Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT)

We propose an effective and robust algorithm for identifying partial differential equations (PDEs) with space-time varying coefficients from the noisy observation of a single solution trajectory. Identifying unknown differential equations from noisy data is a difficult task, and it is even more challenging with space and time varying coefficients in the PDE. The proposed algorithm, GP-IDENT, has three ingredients: (i) we use B-spline bases to express the unknown space and time varying coefficients, (ii) we propose Group Projected Subspace Pursuit (GPSP) to find a sequence of candidate PDEs with various levels of complexity, and (iii) we propose a new criterion for model selection using the Reduction in Residual (RR) to choose an optimal one among a pool of candidates. The new GPSP considers group projected subspaces which is more robust than existing methods in distinguishing correlated group features. We test GP-IDENT on a variety of PDEs and PDE systems, and compare it with the state-of-the-art parametric PDE identification algorithms under different settings to illustrate its outstanding performance. Furthermore, our experiments show that GP-IDENT is effective in identifying the correct terms from a large dictionary, and our model selection scheme is robust to noise.

Data-driven method↗

Influence of pseudopotentials on excitation energies from selected configuration interaction and diffusion Monte Carlo

Due to their diverse nature, the faithful description of excited states within electronic structure theory methods remains one of the grand challenges of modern theoretical chemistry. Quantum Monte Carlo (QMC) methods have been applied very successfully to ground state properties but still remain generally less effective than other non-stochastic methods for electronically excited states. Nonetheless, we have recently reported accurate excitation energies for small organic molecules at the fixed-node diffusion Monte Carlo (FN-DMC) within a Jastrow-free QMC protocol relying on a deterministic and systematic construction of nodal surfaces using the selected configuration interaction (sCI) algorithm known as CIPSI (Configuration Interaction using a Perturbative Selection made Iteratively). Albeit highly accurate, these all-electron calculations are computationally expensive due to the presence of core electrons. One very popular approach to remove these chemically-inert electrons from the QMC simulation is to introduce pseudopotentials (also known as effective core potentials). Taking the water molecule as an example, we investigate the influence of Burkatzki-Filippi-Dolg (BFD) pseudopotentials and their associated basis sets on vertical excitation energies obtained with sCI and FN-DMC methods. Although these pseudopotentials are known to be relatively safe for ground state properties, we evidence that special care may be required if one strives for highly accurate vertical transition energies. Indeed, comparing all-electron and valence-only calculations, we show that using pseudopotentials with the associated basis sets can induce differences of the order of 0.05 eV on the excitation energies. Fortunately, a reasonable estimate of this shift can be estimated at the sCI level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In vitro prototyping of limonene biosynthesis using cell-free protein synthesis

Metabolic engineering of microorganisms to produce sustainable chemicals has emerged as an important part of the global bioeconomy. Unfortunately, efforts to design and engineer microbial cell factories are challenging because design-build-test cycles, iterations of re-engineering organisms to test and optimize new sets of enzymes, are slow. To alleviate this challenge, we demonstrate a cell-free approach termed in vitro Prototyping and Rapid Optimization of Biosynthetic Enzymes (or iPROBE). In iPROBE, a large number of pathway combinations can be rapidly built and optimized. The key idea is to use cell-free protein synthesis (CFPS) to manufacture pathway enzymes in separate reactions that are then mixed to modularly assemble multiple, distinct biosynthetic pathways. As a model, we apply our approach to the 9-step heterologous enzyme pathway to limonene in extracts from Escherichia coli. In iterative cycles of design, we studied the impact of 54 enzyme homologs, multiple enzyme levels, and cofactor concentrations on pathway performance. In total, we screened over 150 unique sets of enzymes in 580 unique pathway conditions to increase limonene production in 24 h from 0.2 to 4.5 mM (23–610 mg/L). Finally, to demonstrate the modularity of this pathway, we also synthesized the biofuel precursors pinene and bisabolene. Finally, we anticipate that iPROBE will accelerate design-build-test cycles for metabolic engineering, enabling data-driven multiplexed cell-free methods for testing large combinations of biosynthetic enzymes to inform cellular design.

59 BASIC BIOLOGICAL SCIENCES↗

Integrated Metrics for County-Level Resilience Ranking Using Entropy and TOPSIS

In the face of atypical weather events, power infrastructure failures, and limited resources for resilience investment, energy decision-makers need data-driven metrics to allocate resilience investments and maximize the reduction of power outage impacts. For state-level planning, for instance, ranking the resilience of each county is key to ensuring effective distribution of resources. In such cases, resilience for each spatial unit is multifaceted and is captured by a set of indicators (i.e., metrics) that can be combined into an overall score that reduces the complexity of power outage dynamics to a single decision metric. However, weighting of these indicators is often addressed by simplifying assumptions (i.e., equal weights) or semi-subjective methods that rely on user-defined weights that can introduce biases (e.g., weighted average score). Within the disaster risk reduction and resilience engineering community, a recurring challenge in multicriteria decision-making is the objective weighting of indicators for composite indices. To address this issue, we have leveraged a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) combined with an entropy-based weighting approach to calculated the integrated scores. This method objectively determines the importance of each metric, better discerns between spatial units (i.e., counties), and offers a more reliable ranking of counties according to their relative resilience attributes. By improving methods for integrating resilience indicators, our approach helps planners and decision-makers prioritize resources more effectively for more efficient resilience investments.

Bhusal, Narayan [Oak Ridge National Laboratory (OR↗