Search NASA⌕ Search

SEARCH · Search NASA

Results for “Batch processing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Hydrotreatment of Nylon 66 and Amide Model Compounds Over Sulfided NiMo Catalysts

Molybdenum sulfide-based catalysts, such as nickel–molybdenum on alumina (NiMoS x /Al 2 O 3 ), are widely used in hydrotreating and have potential for catalyzing waste plastic conversion via hydrogenolysis, yet their performance, such as reaction kinetics and network, for amide-rich polymer feeds is poorly defined. Here we combine Nylon 66 with the amide model compound, N,N-dibutylhexanediamide (DBDAD), to quantify hydrodeoxygenation (HDO) and hydrodenitrogenation (HDN) chemistry in a stirred batch reactor (53 bar H 2 , 280–320°C). DBDAD conversion is near-linear with time, indicating strong adsorption of the substrates on the active sites. Time-resolved product identification indicates parallel C─O first-cleavagedeoxygenation (DO) and C─N first-cleavagedenitrogenation (DN) sequences proceeding through amine and diol intermediates, respectively, to C 4 ─C 6 alkanes. Increasing temperature shifts selectivity toward DN, decreasing the initial r(DO)/r(DN) from 1.38 (280°C) to 0.69 (320°C), with an apparent activation energy of 173 kJ mol −1 for DBDAD conversion. At 300°C, nylon 66 converts faster than DBDAD, producing a complex mixture of oxygen- and nitrogen-containing species and an initial rate ratio r(DO)/r(DN) of 1.6. No heteroaromatic nitrogen products are detected by the method used. These results provide reaction pathways and product signatures relevant to hydro-processing catalysts exposed to polyamide-derived streams.

Nylon 66↗
DOE OSTI2024

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗
NASA NTRS2019

Agile Approach to Assuring the Safety-Critical Embedded Software for NASA's Orion Spacecraft

Human-rated missions like those in NASA's Orion Program continue to grow in complexity. The role of software in achieving ambitious mission objectives has expanded dramatically in the last few decades. Assuring the safety and performance of the embedded flight software is quickly growing beyond the reach of traditional methods and resource levels. The methods used to build these software-dominant systems evolve in an on-going attempt to keep pace with the scope of our ambitions. Agile software development is now commonplace. The long timelines and large batches of work associated with traditional methods are being replaced by rapid delivery of small increments _ as system capabilities are realized in waves. Assurance of these critical software capabilities must therefore conquer an ever-expanding frontier of challenges, and do so with an approach matched to the evolving development methods. This paper recounts the journey of the Orion Independent Verification and Validation (IV&V) team as we addressed this dynamic environment. Widening our aperture to encompass a dramatically larger mission scope, while adjusting our cadence to synchronize with the rapid pace of agile software development, a new approach to IV&V is emerging. This approach is characterized by a sharper focus on mission capabilities, matched with a method to dynamically _follow the risk' as the IV&V team delivers more compelling assurance data in waves. Traditional methods prevalent in IV&V tend to scope the work using artifacts of the development process as they evolve from preliminary to final versions, and the pace of delivery was synchronized with the development timelines prevalent in the waterfall lifecycle. That more static approach is out of phase with the demands of the new environment. Scoping work according to the critical capabilities of the system (rather than artifacts of development) and synchronizing with the rapid pace of agile development, we are moving toward more effective parity with the demands of the environment. We explain the concrete steps we took, the principles that motivated our choices, and the results we have achieved to date.

Capability based assurance↗
DOE OSTI2026

Hydrogen production from full-strength corn stover fermentation effluent in single-chamber replaceable-cathode microbial electrolysis cells

Lignocellulosic residual biomass generated by the agricultural sector is an abundant feedstock for biohydrogen production via dark fermentation. However, this process is intrinsically inefficient, converting only ~30% of the reductant energy into H2 and leaving substantial amounts of reduced byproducts. These byproducts, mostly found in the fermentation effluents, can be further valorized in microbial electrolysis cells (MECs) to enhance the overall H2 recovery. However, current MEC configurations are typically dual- or single-chamber systems, yet both suffer from key inefficiencies. Dual-chamber systems rely on proton exchange membranes that are costly and prone to rapid biofouling, whereas single-chamber, membraneless systems are limited by reduced productivity due to H2 recycling and methanogenic consumption In this study, three single-chamber, 50-mL replaceable-cathode microbial electrolysis cells (RC-MECs) were 3D-printed and equipped with a physical separator to isolate anode and cathode compartments and limit H2 migration. Full-strength milled corn stover (MCS) fermentation effluent (COD of ~23.8 g-COD/L) was treated in fed-batch mode over two operational periods spanning 21 (Run 1) and 80 (Run 2) days. The RC-MECs exhibited comparable performance in both runs: after biofilm maturation, current densities exceeded 100 A/m²_cathode, COD removal reached up to 43%. Notably, extended RC-MECs operation led to a substantial methanogenic activity with the CH4 fraction in the cathode gas increasing to as high as 80% of the total biogas. Additions of a methanogenesis inhibitor 2-bromoethanesulfonate (2-BES) produced transient increases in hydrogen yields (11.51 and 5.12 L-H2/L_reactor/day in Runs 1 and 2, respectively); however, sustained 2-BES addition in subsequent cycles reduced total biogas production, decreased COD removal, and led to volatile fatty acid accumulation. Overall, single-chamber MECs can treat high-strength dark fermentation effluents while improving H2 recovery, but methanogenesis remains a key bottleneck, and complete long-term inhibition may be operationally unsustainable.

Hydrogen Production↗
NASA NTRS1993

The attitude accuracy consequences of on-orbit calibration of the Extreme Ultraviolet Explorer attitude sensors by the Flight Dynamics Facility at Goddard Space Flight Center

The science mission of the Extreme Ultraviolet Explorer (EUVE) requires attitude solutions with uncertainties of 27, 16.7, 16.7 arcseconds (3 sigma) around the roll, pitch, and yaw axes, respectively. The primary input to the attitude determination process is provided by two NASA standard fixed-head star trackers (FHSTs) and a Teledyne dry rotor inertial reference unit (DRIRU) 2. The attitude determination requirements approach the limits attainable with the FHSTs and DRIRU. The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) designed and executed calibration procedures that far exceeded the extent and the data volume of any other FDF-supported mission. The techniques and results of this attempt to obtain attitude accuracies at the limit of sensor capability and the results of analysis of the factors that limit the attitude accuracy are the primary subjects of this paper. The success of the calibration effort is judged by the resulting measurement residuals and comparisons between ground- and onboard-determined attitudes. The FHST star position residuals have been reduced to less tha 4 arcsec per axis -- a value that appears to be limited by the sensor capabilities. The FDF ground system uses a batch least-squares estimator to determine attitude. The EUVE onboard computer (OBC) uses an extended Kalman filter. Currently, there are systematic differences between the two attitude solutions that occasionally exceed the mission requirements for 3 sigma attitude uncertainty. Attempts to understand and reduce these differences are continuing.

Hashmall, J.↗
DOE OSTI2025

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Abstract Machine‐learning (ML) parameterizations of subgrid processes (here of turbulence, convection, and radiation) may one day replace conventional parameterizations by emulating high‐resolution physics without the cost of explicit simulation. However, uncertainty about the relationship between offline and online performance (i.e., when integrated with a large‐scale general circulation model) hinders their development. Much of this uncertainty stems from limited sampling of the noisy, emergent effects of upstream ML design decisions on downstream online hybrid simulation. Our work rectifies the sampling issue via the construction of a semi‐automated, end‐to‐end pipeline for size ensembles of hybrid simulations, revealing important nuances in how systematic reductions in offline error manifest in changes to online error and online stability. For example, removing dropout and switching from a Mean Squared Error to a Mean Absolute Error loss both reduce offline error, but they have opposite effects on online error and online stability. Other design decisions, like incorporating memory, converting moisture input from specific humidity to relative humidity, using batch normalization, and training on multiple climates do not come with any such compromises. Finally, we show that ensemble sizes of may be necessary to reliably detect causally relevant differences online. By enabling rapid online experimentation at scale, we can empirically settle debates regarding subgrid ML parameterization design that would have otherwise remained unresolved in the noise.

Lin, Jerry [Department of Earth System Sciences Un↗
DOE OSTI2026

Raw_data_Batch_I: Argonne to Shorewood via I-55

Date of collection: May 12, 2023 Location: Interstate 55, DuPage County, IL This data set contains lidar and vision data collected along a round trip between I-55 Exit 273A and Exit 253. The data contains the following Robot Operating System (ROS) topics: - /Central_Camera_blurred – Image flow from coaxial camera heading, vehicle front. - /Left_Camera_blurred – Image flow from left camera, 60° from central camera on the left side. - /Right_Camera_blurred – Image flow from right camera, 60° from central camera on the right side. - /camera0/camera_info – Intrinsic and distortion information of left camera. - /camera0/projection_matrix – Extrinsic matrix of left camera from lidar. - /camera2/camera_info – Intrinsic and distortion information of central camera. - /camera2/projection_matrix – Extrinsic matrix of central camera from lidar. - /camera5/camera_info – Intrinsic and distortion information of right camera. - /camera5/projection_matrix – Extrinsic matrix of right camera from lidar. - /novatel/oem7/bestpos – Latitude, longitude, and elevation information from NovAtel GNSS-INS system. - /points_raw – VLP-32 lidar point cloud. - /tf – Vehicle base frame. The data are organized into a data description file and one or more ROS .bag files, dependent on original file size. The data description file provides information about the data collection date, location, and detailed mapping, while the .bag file(s) contain the actual data. Please note that for the purpose of securing personally identifiable information, all license plates and faces included in this publication have been intentionally blurred during real-time processing. ![argonne shorewood image](argone-shorewood.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Volumetric Assessment of UPRITE Exercises From Marker-Based Motion Capture

BACKGROUND Lack of volumetric data on full-body movement of exercises presents a challenge to ensuring the fit of crew member’s full range of motion on the International Space Station (ISS). The Upright Proprioception Retention via In-flight Training and Evaluation (UPRITE) is a sensorimotor countermeasure device designed for maintaining crew members’ proprioception in a microgravity environment. A footplate—attached to a static base—rotates in two degrees of freedom (pitch and roll) up to a 20 deg angle. An initial volumetric assessment assuming an upright standing posture produced a cone-like shape with a narrow bottom and wide top. Such general volumetric assessments risk creating an overly conservative volume estimate, taking up more space than is necessary on the already limited interior space of the ISS, and neglecting necessary volume due to oversimplifying assumptions. Rather, higher-fidelity volumetric assessments offer more comprehensive insights in an environment where every area counts. The main objective of this work is to provide the spatial parameters of exercises on the UPRITE such that it is placed on the ISS according to its volumetric demands or that usage is adjusted to fit the available space. METHODS In 2023, a data collection was performed originally to inform loads and dynamics of system use and was recently leveraged for volumetric assessment. Three human subjects representing different body types (~63-76 inches in stature) performed a variety of board manipulations using UPRITE with body weight offload. The test collected the 3D positional data of a modified full-body Plug-in Gait marker set [1] via a 16-camera OptiTrack MoCap system. After processing – filling marker gaps and trimming data – in OptiTrack Motive, the recorded marker location data, which included device markers, was exported to a readable trajectory file. To accurately represent the full volume defining landmarks, additional markers were digitally added to an unscaled Modified Full Body Model [2]. The model was then scaled according to its subject parameters upon which an inverse kinematics analysis was performed. A custom plugin yielded model marker location data files. Volumetric analyses were performed on the recorded trajectory and model trajectory files using a custom Python-built tool that extracted the marker location data and plotted it in a 3D space. Concerned with only the maximum volume of the motion, a 3D convex hull analysis was applied to the plot, extracting the vertices or external points of the eventual 3D CAD output, dubbed aptly as a “volume shell”. This overall approach was based on guidance in a NASA-STD-3001 Technical Brief [3]. RESULTS AND DISCUSSION Batch volumetric assessment on the exercises for each subject was performed, producing high-fidelity volume shells in minimal time. Preliminary results highlighted the value in higher-fidelity volumes based on collected data when possible. For example, revolving a single posture in the cone assessment would not have sufficiently captured a single leg stance; rather, it would need to involve swinging the leg both forward and back. Additional observations and the maximal dimensions of the volumes, including those based on scaled data for ISS anthropometric requirements, will be presented at the Human Research Program Investigator’s Workshop. CONCLUSIONS While this work’s primary objective was for the UPRITE-to-ISS integration, the tool built to conduct this analysis has wide applications for future exercise systems as an informational tool for optimal device placement. The tool and its findings also have implications for exercise device design and spacecraft interior considerations on Gateway, the Lunar Pressurized Rover, and beyond. REFERENCES [1] Bell, C. A., et al. (2023) Recent Improvements and Verification of a Full Body Model in OpenSim. NASA Human Research Program Investigator’s Workshop. https://ntrs.nasa.gov/citations/20230001080 [2] Lostroscio, K., et al (2023) The Digital Astronaut Simulation. AHFE International Conference on Human Factors in Design, Engineering, and Computing for All. [3] Exercise Overview. (2023) NASA-STD-3001 Technical Brief. https://www.nasa.gov/wp-content/uploads/2023/12/ochmo-tb-031-exercise-overview.pdf?emrc=9d454c?emrc=9d454c

L D Quinto↗
DOE OSTI2026

Robust Containment Queries over Collections of Trimmed NURBS Surfaces via Generalized Winding Numbers

Here, we propose a containment query that is robust to the watertightness of regions bound by trimmed NURBS surfaces, as this property is difficult to guarantee for in-the-wild CAD models. Containment is determined through the generalized winding number (GWN), a mathematical construction that is indifferent to the arrangement of surfaces in the shape. Applying contemporary techniques for the 3D GWN to trimmed NURBS surfaces requires some form of geometric discretization, introducing computational inefficiency to the algorithm and even risking containment misclassifications near the surface. In contrast, our proposed method leverages properties of the 3D solid angle to solve the relevant surface integral using a boundary formulation with rapidly converging adaptive quadrature. Batches of queries are further accelerated by memoizing (i.e., caching and reusing) quadrature node positions and tangents as they are evaluated. We demonstrate that our GWN method is robust to complex trimming geometry in a CAD model, and is accurate up to arbitrary precision at arbitrary distances from the surface. The derived containment query is therefore robust to model non-watertightness while respecting all curved features of the input shape.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1999

Boronate affinity adsorption of RNA: possible role of conformational changes

Batch equilibrium adsorption isotherm determination is used to characterize the adsorption of mixed yeast RNA on agarose-immobilized m-aminophenylboronic acid. It is shown that the affinity-enhancing influence of divalent cations depends strongly on the precise nature of the cation used, with barium being far more effective than the conventionally-used magnesium. This adsorption-promoting influence of barium is suggested to arise primarily from ionic influences on the structure and rigidity of the RNA molecule, as the adsorption of ribose-based small molecules is not similarly affected. The substitution of barium for the standard magnesium counterion does not greatly promote the adsorption of DNA, implying that the effect is specific to RNA and may be useful in boronate-based RNA separations. RNA adsorption isotherms exhibit sharp transitions as functions of temperature, and these transitions occur at different temperatures with Mg2+ and with Ba2+. Adsorption affinity and capacity were found to increase markedly at lower temperatures, suggestive of an enthalpically favored interaction process. The stoichiometric displacement parameter, Z, in Ba2+ buffer is three times the value in Mg2+ buffer, and is close to unity.

NASA Discipline Environmental Health↗
DOE OSTI2024

Insights into the Surface Electronic Structure and Catalytic Activity of InO x /Au(111) Inverse Catalysts for CO 2 Hydrogenation to Methanol

In this article, the direct conversion of carbon dioxide (CO 2 ) into methanol (CH 3 OH) via low-temperature hydrogenation is crucial for recycling anthropogenic CO 2 emissions and producing fuels or high value chemicals. Nevertheless, it continues to be a great challenge due to the trade-off between selectivity and catalytic activity. For CO 2 hydrogenation, In 2 O 3 catalysts are known for their high CH 3 OH selectivity. Subsequent studies explored depositing metals on In 2 O 3 to enhance CO 2 conversion. Despite extensive research on metal (M) supported In 2 O 3 catalysts, the role of In-M alloys and M/In 2 O 3 interfaces in CO 2 activation and CH 3 OH selectivity remains unclear. In this work, we have examined the behavior of In/Au(111) alloys and InO x /Au(111) inverse systems during CO 2 hydrogenation using synchrotron-based ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) and catalytic tests in a batch reactor. Indium forms alloys with Au(111) after deposition. The In-Au(111) alloys display high reactivity towards CO 2 and can dissociate the molecule at room temperature to generate InO x nanostructures. At very low coverages of In (≤ 0.05 ML), the InO x nanostructures are not stable under CO 2 hydrogenation conditions and the active In-Au(111) alloys produces mainly CO and little methanol. An increase in indium coverage to 0.3 ML led to stable InOx nanostructures under CO 2 hydrogenation conditions. These InO x /Au(111) catalysts displayed a high selectivity (~ 80 %) towards CH 3 OH production and an activity for CO 2 conversion that was at least 10 times larger than that of plain In 2 O 3 or Cu(111) and Cu/ZnO(000$\overline{1)}$ benchmark catalysts. The results of AP-XPS show that InO x /Au(111) produces methanol via methoxy intermediates. Inverse oxide/metal catalysts containing InOx open up a possibility for improving CO 2 → CH 3 OH conversion in processes associated with the control of environmental pollution and the production of high value chemicals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hybrid HEFA-HDCJ Process for the Production of Jet Fuel Blendstocks

The hydrotreatment of bio-oil derived from the pyrolysis and biocrude from hydrothermal liquefaction of lignocellulosic materials to produce hydrocarbons faces significant technological challenges, mainly due to the high reactivity and poor thermal stability of bio-oil, resulting in the formation of large quantities of coke. This problem has been addressed by existing PNNL patents with a two-step hydrotreatment technology in which the bio-oil is first stabilized with a noble hydrogenation metal (often Pt or Ru). Then, in the second step, the bio-oil is deoxygenated with a Ni-Mo or Co-Mo sulfide catalyst. The main problem with this approach is that the Pt/Ru catalysts deactivate easily in the presence of S or other impurities, which are commonly present in pyrolysis oils. In this project, we explored technological solutions to mitigate coke formation, avoiding the use of Pt/Ru catalysts. Our strategy is based on three actions: (1) Bio-oil stabilization in the presence of alcohols. In this project, we studied the stabilization with butanol. (2) the use of a cosolvent to solubilize the bio-oil. Because coke formation reactions are second-order reactions a reduction in the concentration of reactive bio-oil molecules. In this case, we used yellow greases as a co-solvent. (3) Separation of bio-oil reactive fractions. In this project, we studied the removal of water-soluble fractions. Our batch co-hydrotreatment studies confirmed that the addition of butanol and methanol and the blend with lipids effectively contributed to mitigating coke formation (reducing coke yield to about 1 wt.% %). The removal of sugars did not have a noticeable effect on the overall coke yield, suggesting that coke precursors are present in all bio-oil fractions.

09 BIOMASS FUELS↗
NASA NTRS1994

Basalt generation at the Apollo 12 site. Part 2: Source heterogeneity, multiple melts, and crustal contamination

The petrogenesis of Apollo 12 mare basalts has been examined with emphasis on trace-element ratios and abundances. Vitrophyric basalts were used as parental compositions for the modeling, and proportions of fractionating phases were determined using the MAGFOX prograqm of Longhi (1991). Crystal fractionation processes within crustal and sub-crustal magma chambers are evaluated as a function of pressure. Knowledge of the fractionating phases allows trace-element variations to be considered as either source related or as a product of post-magma-generation processes. For the ilmenite and olivine basalts, trace-element variations are inherited from the source, but the pigeonite basalt data have been interpreted with open-system evolution processes through crustal assimilation. Three groups of basalts have been examined: (1) Pigeonite basalts-produced by the assimilation of lunar crustal material by a parental melt (up to 3% assimilation and 10% crystal fractionation, with an 'r' value of 0.3). (2) Ilmenite basalts-produced by variable degrees of partial melting (4-8%) of a source of olivine, pigeonite, augite, and plagioclase, brought together by overturn of the Lunar Magma Ocean (LMO) cumulate pile. After generation, which did not exhaust any of the minerals in the source, these melts experienced closed-system crystal fractionation/accumulation. (3) Olivine basalts-produced by variable degrees of partial melting (5-10%) of a source of olivine, pigeonite, and augite. After generation, again without exhausting any of the minerals in the source, these melts evolved through crystal accumulation. The evolved liquid counterparts of these cumulates have not been sampled. The source compositions for the ilmenite and olivine basalts were calculated by assuming that the vitrophyric compositions were primary and the magmas were produced by non-modal batch melting. Although the magnitude is unclear, evaluation of these source regions indicates that both be composed of early- and late-stage Lunar Magma Ocean (LMO) cumulates, requiring an overturn of the cumulate pile.

Neal, Clive R.↗
DOE OSTI2025

Decision-Model Supported Algal Cultivation Process Enhancement (DMSACPE) (Final Technical Report)

This project was proposed in response to the FY19 Bioenergy Technologies Office Multi-Topic Funding Opportunity Announcement DE-FOA-0002029, Area of Interest Subtopic 1 (AOI1): Cultivation Intensification Processes for Algae. The main challenge identified by the FOA was “in translating results between laboratory research systems and larger-scale outdoor (or mass culture) systems. These difficulties limit reliable experimental durations, adequate and representative experimental volumes of material, and results that can be reproduced reliably. By overcoming the challenge in translating results between laboratory and mass cultures, the objective of AOI 1 is to increase the harvest yield, robustness, and quality of algae cultivation for biofuels and bioproducts”. This report marks the final technical deliverable of this project and reviews all the major findings of the research program.

09 BIOMASS FUELS↗
DOE OSTI2026

Raw_data_Batch_I: State Street

Date of collection: May 18, 2023 Location: State Street, Chicago, IL This data set contains lidar and vision data collected along State Street. The vehicle started from outside of the McCormick Tribune Campus Center at the Illinois Institute of Technology’s Mies Campus and headed north along State Street, until the north end of State Street in the Gold Coast. The data contains the following Robot Operating System (ROS) topics: - /Central_Camera_blurred – Image flow from coaxial camera heading, vehicle front. - /Left_Camera_blurred – Image flow from left camera, 60° from central camera on the left side. - /Right_Camera_blurred – Image flow from right camera, 60° from central camera on the right side. - /camera0/camera_info – Intrinsic and distortion information of left camera. - /camera0/projection_matrix – Extrinsic matrix of left camera from lidar. - /camera2/camera_info – Intrinsic and distortion information of central camera. - /camera2/projection_matrix – Extrinsic matrix of central camera from lidar. - /camera5/camera_info – Intrinsic and distortion information of right camera. - /camera5/projection_matrix – Extrinsic matrix of right camera from lidar. - /novatel/oem7/bestpos – Latitude, longitude, and elevation information from NovAtel GNSS-INS system. - /points_raw – VLP-32 lidar point cloud. - /tf – Vehicle base frame. The data are organized into a data description file and one or more ROS .bag files, dependent on original file size. The data description file provides information about the data collection date, location, and detailed mapping, while the .bag file(s) contain the actual data. Please note that for the purpose of securing personally identifiable information, all license plates and faces included in this publication have been intentionally blurred during real-time processing. ![state street image](state-street.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Raw_data_Batch_I: Ashland Avenue

Date of collection: May 26, 2023 Location: Ashland Avenue, Chicago, IL This data set contains lidar and vision data collected along Ashland Avenue. A south-to-north run starts from the intersection of Irving Park and Ashland and ends at Andersonville Garden. A north-to-south run starts from Andersonville Garden and ends around the intersection of Irving Park and Ashland. The data contains the following Robot Operating System (ROS) topics: - /Central_Camera_blurred – Image flow from coaxial camera heading, vehicle front. - /Left_Camera_blurred – Image flow from left camera, 60° from central camera on the left side. - /Right_Camera_blurred – Image flow from right camera, 60° from central camera on the right side. - /camera0/camera_info – Intrinsic and distortion information of left camera. - /camera0/projection_matrix – Extrinsic matrix of left camera from lidar. - /camera2/camera_info – Intrinsic and distortion information of central camera. - /camera2/projection_matrix – Extrinsic matrix of central camera from lidar. - /camera5/camera_info – Intrinsic and distortion information of right camera. - /camera5/projection_matrix – Extrinsic matrix of right camera from lidar. - /novatel/oem7/bestpos – Latitude, longitude, and elevation information from NovAtel GNSS-INS system. - /points_raw – VLP-32 lidar point cloud. - /tf – Vehicle base frame. The data are organized into a data description file and one or more ROS .bag files, dependent on original file size. The data description file provides information about the data collection date, location, and detailed mapping, while the .bag file(s) contain the actual data. Please note that for the purpose of securing personally identifiable information, all license plates and faces included in this publication have been intentionally blurred during real-time processing. ![ashland avenue image](ashland-avenue.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Raw_data_Batch_I: Lisle to Waterfall Glen

Date of collection: May 11, 2023 Location: DuPage County, IL This dataset contains lidar and vision data collected between Lisle, IL, and the Waterfall Glen parking lot. The vehicle started near Cass School District 63, headed east along IL 34. The vehicle then turned south along IL 83 until Interstate 55. Finally, the vehicle turned southwest along I 55 until Exit 273A and headed toward the Waterfall Glen parking lot. The data contains the following Robot Operating System (ROS) topics: - /Central_Camera_blurred – Image flow from coaxial camera heading, vehicle front. - /Left_Camera_blurred – Image flow from left camera, 60° from central camera on the left side. - /Right_Camera_blurred – Image flow from right camera, 60° from central camera on the right side. - /camera0/camera_info – Intrinsic and distortion information of left camera. - /camera0/projection_matrix – Extrinsic matrix of left camera from lidar. - /camera2/camera_info – Intrinsic and distortion information of central camera. - /camera2/projection_matrix – Extrinsic matrix of central camera from lidar. - /camera5/camera_info – Intrinsic and distortion information of right camera. - /camera5/projection_matrix – Extrinsic matrix of right camera from lidar. - /novatel/oem7/bestpos – Latitude, longitude, and elevation information from NovAtel GNSS-INS system. - /points_raw – VLP-32 lidar point cloud. - /tf – Vehicle base frame. The data are organized into a data description file and one or more ROS .bag files, dependent on original file size. The data description file provides information about the data collection date, location, and detailed mapping, while the .bag file(s) contain the actual data. Please note that for the purpose of securing personally identifiable information, all license plates and faces included in this publication have been intentionally blurred during real-time processing. ![lisle waterfall image](lisle-waterfall.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design

Access to reliable, clean energy sources is a major concern for national security. Much research is focused on the “grand challenge” of producing energy via controlled fusion reactions in a laboratory setting. For fusion experiments, specifically inertial confinement fusion (ICF), to produce sufficient energy, the fusion reactions in the ICF fuel need to become self-sustaining and burn deuterium-tritium (DT) fuel efficiently. The recent record-breaking NIF ignition shot was able to achieve this goal as well as produce more energy than used to drive the experiment. This achievement brings self-sustaining fusion-based power systems closer than ever before, capable of providing humans with access to secure, renewable energy. In order to further progress toward the actualization of such power systems, more ICF experiments need to be conducted at large laser facilities such as the United States's National Ignition Facility (NIF) or France's Laser Mega-Joule. The high cost per shot and limited number of shots that are possible per year make it prohibitive to perform large numbers of experiments. As such, experimental design relies heavily on complex predictive physics simulations for high-fidelity “preshot” analysis. These multidimensional, multi-physics, high-fidelity simulations have to account for a variety of input parameters as well as modeling the extreme conditions (pressures and densities) present at ignition. Such simulations (especially in 3D) can become computationally prohibitive to turn around for each ICF experiment. In this work, we explore using Bayesian optimization with Gaussian processes (GPs) to find optimal designs for ICF double shell targets, while keeping computational costs to manageable levels. These double shell targets have an inner shell that grades from beryllium on the outer surface to the higher Z material molybdenum, as opposed to the nominally used tungsten, on the inside in order to trade off between the high performance associated with high density inner shells and capsule stability. We describe our results for “capsule-only” xRAGE simulations to study the physics between different capsule designs, inner shell materials, and potential for future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗