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At least 955 records · Page 53

Space Shuttle wind tunnel testing program

A major phase of the Space Shuttle Vehicle (SSV) Development Program was the acquisition of data through the space shuttle wind tunnel testing program. It became obvious that the large number of configuration/environment combinations would necessitate an extremely large wind tunnel testing program. To make the most efficient use of available test facilities and to assist the prime contractor for orbiter design and space shuttle vehicle integration, a unique management plan was devised for the design and development phase. The space shuttle program is reviewed together with the evolutional development of the shuttle configuration. The wind tunnel testing rationale and the associated test program management plan and its overall results is reviewed. Information is given for the various facilities and models used within this program. A unique posttest documentation procedure and a summary of the types of test per disciplines, per facility, and per model are presented with detailed listing of the posttest documentation.

Whitnah, A. M.↗

Development and refinement of test bed simulations

Lewis Research Center of NASA, with support from Rocketdyne, was engaged in non-real time computer simulation effort for the Space Station Freedom Electric Power System (EPS) EASY5, a simulation package, is used as the primary tool for this activity. Early in the design of the EPS, two test beds were set up at Lewis. The Integrated Test Bed (ITB), that combines and upgrades these test beds, is in the planning stage. The test beds are designed to functionally represent many of the components of the EPS and their interconnections. The simulation effort is primarily directed towards these test beds. Model verification is performed using test bed data.

Dravid, Narayan V.↗

Product assurance technology for procuring reliable, radiation-hard, custom LSI/VLSI electronics

Advanced measurement methods using microelectronic test chips are described. These chips are intended to be used in acquiring the data needed to qualify Application Specific Integrated Circuits (ASIC's) for space use. Efforts were focused on developing the technology for obtaining custom IC's from CMOS/bulk silicon foundries. A series of test chips were developed: a parametric test strip, a fault chip, a set of reliability chips, and the CRRES (Combined Release and Radiation Effects Satellite) chip, a test circuit for monitoring space radiation effects. The technical accomplishments of the effort include: (1) development of a fault chip that contains a set of test structures used to evaluate the density of various process-induced defects; (2) development of new test structures and testing techniques for measuring gate-oxide capacitance, gate-overlap capacitance, and propagation delay; (3) development of a set of reliability chips that are used to evaluate failure mechanisms in CMOS/bulk: interconnect and contact electromigration and time-dependent dielectric breakdown; (4) development of MOSFET parameter extraction procedures for evaluating subthreshold characteristics; (5) evaluation of test chips and test strips on the second CRRES wafer run; (6) two dedicated fabrication runs for the CRRES chip flight parts; and (7) publication of two papers: one on the split-cross bridge resistor and another on asymmetrical SRAM (static random access memory) cells for single-event upset analysis.

Buehler, M. G.↗

Development and refinement of test bed simulations

Lewis Research Center of NASA, with support from Rocketdyne, has engaged in a nonreal-time computer simulation effort for the Space Station Freedom Electric Power System (EPS). EASYS, a simulation package, is used as the primary tool for this activity. Early in the design of the EPS, two test beds were set up at Lewis. The Integrated Test Bed (ITB) that combines and upgrades these test beds is in the planning stage. The test beds are designed to functionally represent many of the components of the EPS and their interconnections. The simulation effort is primarily directed towards these test beds. Model verification is performed using test bed data.

Dravid, N. V.↗

SGR J1550-5418 Bursts Detected with the Fermi Gamma-Ray Burst Monitor during Its Most Prolific Activity

We have performed detailed temporal and time-integrated spectral analysis of 286 bursts from SGR J1550-5418 detected with the Fermi Gamma-ray Burst Monitor (GBM) in 2009 January, resulting in the largest uniform sample of temporal and spectral properties of SGR J1550-5418 bursts. We have used the combination of broadband and high time-resolution data provided with GBM to perform statistical studies for the source properties.We determine the durations, emission times, duty cycles, and rise times for all bursts, and find that they are typical of SGR bursts. We explore various models in our spectral analysis, and conclude that the spectra of SGR J15505418 bursts in the 8-200 keV band are equally well described by optically thin thermal bremsstrahlung (OTTB), a power law (PL) with an exponential cutoff (Comptonized model), and two blackbody (BB) functions (BB+BB). In the spectral fits with the Comptonized model, we find a mean PL index of -0.92, close to the OTTB index of -1. We show that there is an anti-correlation between the Comptonized E(sub peak) and the burst fluence and average flux. For the BB+BBfits, we find that the fluences and emission areas of the two BB functions are correlated. The low-temperature BB has an emission area comparable to the neutron star surface area, independent of the temperature, while the high temperature BB has a much smaller area and shows an anti-correlation between emission area and temperature.We compare the properties of these bursts with bursts observed from other SGR sources during extreme activations, and discuss the implications of our results in the context of magnetar burst models.

bursts↗

A Physics-Based Modeling Framework for Prognostic Studies

Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles.

Li-ion Batteries↗

Advanced Stirling Convertor Dual Convertor Controller Testing at NASA Glenn Research Center in the Radioisotope Power Systems System Integration Laboratory

NASA Glenn Research Center developed a nonnuclear representation of a Radioisotope Power System (RPS) consisting of a pair of Advanced Stirling Convertors (ASCs), Dual Convertor Controller (DCC) EMs (engineering models) 2 and 3, and associated support equipment, which were tested in the Radioisotope Power Systems System Integration Laboratory (RSIL). The DCC was designed by the Johns Hopkins University Applied Physics Laboratory (JHU/APL) to actively control a pair of ASCs. The first phase of testing included a Dual Advanced Stirling Convertor Simulator (DASCS), which was developed by JHU/APL and simulates the operation and electrical behavior of a pair of ASCs in real time via a combination of hardware and software. RSIL provides insight into the electrical interactions between a representative radioisotope power generator, its associated control schemes, and realistic electric system loads. The first phase of integration testing included the following spacecraft bus configurations: capacitive, battery, and super-capacitor. A load profile, created based on data from several missions, tested the RPS's and RSIL's ability to maintain operation during load demands above and below the power provided by the RPS. The integration testing also confirmed the DCC's ability to disconnect from the spacecraft when the bus voltage dipped below 22 volts or exceeded 36 volts. Once operation was verified with the DASCS, the tests were repeated with actual operating ASCs. The goal of this integration testing was to verify operation of the DCC when connected to a spacecraft and to verify the functionality of the newly designed RSIL. The results of these tests are presented in this paper.

Controllers↗

Data for Filling the Cellulosic Bio-economy Gap by Utilizing a Wedge Approach Combined with Stakeholder Collaboration

The price gap between the market and breakeven prices of cellulosic biomass for farmers represents a significant barrier to the development of a low-carbon cellulosic bioeconomy. Using a bottom-up, agent-based modeling tool that replicates the behaviors and interactions of key stakeholders, this study analyzes the emergence of a cellulosic bioeconomy at the local scale through a wedge approach that examines an integrated portfolio of multiple policy options, including subsidies for small-scale bioproducts and environmental credits. The role of collaboration among multiple stakeholders, such as biomass producers (farmers), bio-refinery industry, government, and society, is assessed for filling the price gap. Using the Sangamon River Basin as a case study site, we evaluate the effectiveness of the wedge approach by comparing simulation results from multiple scenarios, each incorporating different combinations of bioeconomy wedges, with and without stakeholder collaboration. Results underscore that active collaboration among stakeholders acts as a catalyst enlarging the effectiveness of bioeconomy wedges. Including the carbon credits and environmental value in the policy portfolio is found to bridge the price gap through collective contributions from diverse stakeholders, where the cellulosic biofuel and bioproduct industry plays a pivotal role. Although this study is conducted at the local watershed scale, the methodology and findings offer valuable insights for market development in other watersheds and the potential scaling of local markets to regional and national levels.

Economics↗

Event Driven Messaging with Role-Based Subscriptions

Event Driven Messaging with Role-Based Subscriptions (EDM-RBS) is a framework integrated into the Service Management Database (SMDB) to allow for role-based and subscription-based delivery of synchronous and asynchronous messages over JMS (Java Messaging Service), SMTP (Simple Mail Transfer Protocol), or SMS (Short Messaging Service). This allows for 24/7 operation with users in all parts of the world. The software classifies messages by triggering data type, application source, owner of data triggering event (mission), classification, sub-classification and various other secondary classifying tags. Messages are routed to applications or users based on subscription rules using a combination of the above message attributes. This program provides a framework for identifying connected users and their applications for targeted delivery of messages over JMS to the client applications the user is logged into. EDMRBS provides the ability to send notifications over e-mail or pager rather than having to rely on a live human to do it. It is implemented as an Oracle application that uses Oracle relational database management system intrinsic functions. It is configurable to use Oracle AQ JMS API or an external JMS provider for messaging. It fully integrates into the event-logging framework of SMDB (Subnet Management Database).

Bui, Tung↗

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↗

Scramjet Performance Assessment Using Water Absorption Diagnostics (U)

Simultaneous multiple path measurements of temperature and H2O concentration will be presented for the AIMHYE test entries in the NASA Ames 16-Inch Shock Tunnel. Monitoring the progress of high temperature chemical reactions that define scramjet combustor efficiencies is a task uniquely suited to nonintrusive optical diagnostics. One application strategy to overcome the many challenges and limitations of nonintrusive measurements is to use laser absorption spectroscopy coupled with optical fibers. Absorption spectroscopic techniques with rapidly tunable lasers are capable of making simultaneous measurements of mole fraction, temperature, pressure, and velocity. The scramjet water absorption diagnostic was used to measure combustor efficiency and was compared to thrust measurements using a nozzle force balance and integrated nozzle pressures to develop a direct technique for evaluating integrated scramjet performance. Tests were initially performed with a diode laser tuning over a water absorption feature at 1391.7 nm. A second diode laser later became available at a wavelength near 1343.3 nm covering an additional water absorption feature and was incorporated in the system for a two-wavelength technique. Both temperature and mole fraction can be inferred from the lineshape analysis using this approach. Additional high temperature spectroscopy research was conducted to reduce uncertainties in the scramjet application. The lasers are optical fiber coupled to ports at the combustor exit and in the nozzle region. The output from the two diode lasers were combined in a single fiber, and the resultant two-wavelength beam was subsequently split into four legs. Each leg was directed through 60 meters of optical fiber to four combustor exit locations for measurement of beam intensity after absorption by the water within the flow. Absorption results will be compared to 1D combustor analysis using RJPA and nozzle CFD computations as well as to data from a nozzle metric balance measuring thrust and integrated pressure measurements along the length of the nozzle. Assessment of its value as a combustor performance evaluation tool will be conducted.

Cavolowsky, John A.↗

Using pile-up collisions as an abundant source of low-energy hadronic physics processes in ATLAS and an extraction of the jet energy resolution

During the 2015–2018 data-taking period, the Large Hadron Collider delivered proton-proton bunch crossings at a centre-of-mass energy of 13 TeV to the ATLAS experiment at a rate of roughly 30 MHz, where each bunch crossing contained an average of 34 independent inelastic proton-proton collisions. The ATLAS trigger system selected roughly 1 kHz of these bunch crossings to be recorded to disk. Offline algorithms then identify one of the recorded collisions as the collision of interest for subsequent data analysis, and the remaining collisions are referred to as pile-up. Pile-up collisions represent a trigger-unbiased dataset, which is evaluated to have an integrated luminosity of 1.33 pb -1 in 2015–2018. This is small compared with the normal trigger-based ATLAS dataset, but when combined with vertex-by-vertex jet reconstruction it provides up to 50 times more dijet events than the conventional single-jet-trigger-based approach, and does so without adding any additional cost or requirements on the trigger system, readout, or storage. The pile-up dataset is validated through comparisons with a special trigger-unbiased dataset recorded by ATLAS, and its utility is demonstrated by means of a measurement of the jet energy resolution in dijet events, where the statistical uncertainty is significantly reduced for jet transverse momenta below 65 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Automated integration gate selection for Gaussian mixture model pulse shape discrimination

Pulse shapes differ between neutron and gamma particles when measured with detector devices employing pulse shape discriminating (PSD) scintillators. Digitized waveforms can be used in detection systems to perform pulse shape discrimination for this application. Prior Gaussian Mixture Model (GMM) methods require access to the pulse full-waveform. Reducing the waveform to a smaller set of combined samples reduces computational cost while affecting PSD performance. In this work, we develop a method for selecting the best performing combination of integration gates, or contiguous summed segments of the digitized pulse for PSD. The method uses a discrimination score based on the GMM PSD approach. Furthermore, the final selection is performed using Bayesian Optimization. PSD detection results are compared with varying numbers of selected gates on time-of-flight (TOF) data. This method can be used to fully automate the selection of gates in an unsupervised (without ground truth labels) setting.

42 ENGINEERING↗

Extreme-scale EV charging infrastructure planning for last-mile delivery using high-performance parallel computing

Here, this paper addresses stochastic charger location and allocation problems under queue congestion for last-mile delivery using electric vehicles (EVs). The objective is to decide where to open charging stations and how many chargers of each type to install, subject to budgetary and waiting-time constraints. We formulate the problem as a mixed-integer non-linear program, where each station-charger pair is modeled as a multiserver queue with stochastic arrivals and service times to capture the notion of waiting in fleet operations. The model is extremely large, with billions of variables and constraints for a typical metropolitan area; even loading the model in solver memory is difficult, let alone solving it. To address this challenge, we develop a Lagrangian-based dual decomposition framework that decomposes the problem by station and leverages parallelization on high-performance computing systems, where the subproblems are solved by using a cutting plane method and their solutions are collected at the master level. We also develop a three-step rounding heuristic to transform the fractional subproblem solutions into feasible integral solutions. Computational experiments on data from the Chicago metropolitan area with hundreds of thousands of households and thousands of candidate stations show that our approach produces high-quality solutions in cases where existing exact methods cannot even load the model in memory. We also analyze various policy scenarios, demonstrating that combining existing depots with newly built stations under multiagency collaboration substantially reduces costs and congestion. These findings offer a scalable and efficient framework for developing sustainable large-scale EV charging networks.

Capacity allocation↗

On-Demand Column Joining for High Energy Physics

As the Large Hadron Collider (LHC) transitions into the High-Luminosity LHC (HL-LHC) era, the volume of data to be processed is expected to increase significantly. The CMS Experiment currently utilizes various data formats, including AOD, MiniAOD, and NanoAOD, each with different levels of detail and storage requirements. This paper addresses the challenges of data duplication and storage inefficiencies in high-energy physics (HEP) analyses by proposing an on-demand column-joining solution. This approach aims to reduce data duplication by enabling the dynamic combination of NanoAOD data with auxiliary information from larger data tiers, such as MiniAOD. The proposed solution leverages Trino, a high-performance distributed SQL query engine, to perform efficient and scalable data joins. Benchmarks using CMS OpenData demonstrate the feasibility of this approach, showing that it can handle large datasets with low latency. Integration with the scikit-hep ecosystem and the coffea analysis framework is also discussed, highlighting the potential for seamless end-to-end data processing and analysis. Ongoing and future work focuses on expanding benchmarks, integrating ServiceX for data transformation, and exploring the use of native object storage solutions.

Manganelli, Nicholas [Northeastern U.]↗

Machine Learning Atom Probe Tomography Tool For Automatic And Fast Clustering

The software uses a YOLO11 segmentation model trained on synthetic data to analyze APT datasets. The workflow operates as follows: 1. Data Slicing: The APT dataset is divided into multiple 2D cross-sections of a specified thickness. 2. Segmentation: The model identifies point-dense regions within each 2D slice. 3. 3D Reconstruction: Detected regions (masks) from all slices are combined and reconstructed back into the original 3D space, forming clusters. The integration with HPC resources enables the software to process large-scale APT datasets efficiently. This combination of automation and scalability reduces manual intervention, improves reproducibility, and accelerates the clustering workflow.

Tang, Yalei [Idaho National Laboratory (INL), Idah↗

Fully Bayesian Analysis With Model Inadequacy Correction For Nuclear Graphite Property Models With Hierarchical Variance Structure

Nuclear-grade graphites are extensively utilized in the core designs of various advanced nuclear reactors. Within the reactor environment, graphite is subjected to prolonged exposure to extreme conditions, including high temperatures, radiation, and potentially molten salt and oxygen. Such exposure can induce several degradation mechanisms in graphite, such as nonuniform volumetric strains caused by irradiation and thermal expansion, leading to stresses that may compromise the performance of graphite components. Assessing component integrity, forecasting component performance over the reactor's lifespan, and developing design standards necessitate robust tools for predicting fracture initiation and propagation in graphite structural components within nuclear reactors. This code enables the Bayesian calibration of properties for nuclear-grade graphites. Using a hierarchical Bayesian approach, multiple experimental data sources are combined to develop Gaussian process models for the properties. Using the Kennedy O'Hagan framework, the uncertainties due inadequacies in the model and the inherent spread in the experimental data are quantified.

Dhulipala, Som Lakshmi NarasimhaLakshmi Narasimha ↗

SEGUID v2: Extending SEGUID checksums for circular, linear, single- and double-stranded biological sequences

Background Synthetic biology involves combining different DNA fragments, each containing functional biological parts, to address specific problems. Fundamental gene-function research often requires cloning and propagating DNA fragments, such as those from the iGEM Parts Registry or Addgene, typically distributed as circular plasmids. Addgene’s repository alone offers around 150,000 plasmids. To ensure data integrity, cryptographic checksums can be calculated for the sequences. Each sequence has a unique checksum, making checksums useful for validation and quick lookups of associated annotations. For example, the SEGUID checksum uniquely identifies protein sequences with a 27-character string. Objectives The original SEGUID, while effective for protein sequences and single-stranded DNA (ssDNA), is not suitable for circular DNA since there is no natural starting position nor for double-stranded DNA (dsDNA) since two separate sequences are present. Challenges include how to uniquely represent linear dsDNA, circular ssDNA, and circular dsDNA. To meet these needs, we propose SEGUID v2, which extends the original SEGUID to handle additional types of sequences. Conclusions SEGUID v2 produces orientation and rotation invariant checksums for single-stranded, double-stranded, possibly staggered, linear, and circular DNA and RNA sequences. Customizable alphabets allow for other types of sequences. In contrast to the original SEGUID, which uses Base64, SEGUID v2 uses Base64url to encode the SHA-1 hash. This ensures SEGUID v2 checksums can be used as-is in filenames, regardless of platform, and in URLs, with minimal friction. Availability SEGUID v2 is readily available for major programming languages, distributed under the MIT license. JavaScript package seguid is available on npm, Python package seguid on PyPi, R package seguid on CRAN, and a Tcl script on GitHub. These tools, along with documentation, examples, and an online SEGUID Calculator , can be found at https://www.seguid.org .

Pereira, Humberto↗