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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Consequence-driven cyber-informed engineering and related systems and methods

Embodiments of the disclosure relate to a computer-implemented consequence-driven cyber-informed engineering tool for performing and reporting consequence-based prioritization, system-of-systems breakdown, consequence-based targeting, and mitigations and protections. Embodiments of a CCE tool may perform one or more steps of defining a target industrial control system (ICS), wherein the target ICS includes operational goals, critical functions, and critical services; determining one or more scored high consequence events (HCE) associated with the defined target ICS; prioritizing the scored HCEs according to an HCE severity index; and updating a dashboard with one or more representations of the prioritized HCEs, wherein the updated dashboard is associated with the CCE tool and presented at a display.

Assante, Michael↗
DOE OSTI2025

Unconventional compute methods and future challenges for superconducting digital computing

Superconducting digital computing (SDC) based on Josephson junctions (JJs) offers significant potential for enhancing compute throughput and reducing energy consumption compared to conventional room-temperature CMOS-based approaches. Current superconducting logic families exhibit diverse characteristics in clocking strategies, power management, and information encoding techniques. This paper reviews recent advancements in unconventional computing methods specifically designed for superconducting digital circuits, emphasizing temporal computing and pulse-train representations. Notable techniques include race logic (RL), temporal pulse train computing (U-SFQ), and temporal multipliers, each offering unique performance and area advantages suited to superconducting implementations. Additionally, this paper reviews innovations in superconducting coarse-grain reconfigurable architectures (CGRA), superconducting-specific on-chip communication architectures, cryogenic sensor interfaces, and quantum computing control electronics. Finally, we highlight research challenges that should be addressed to facilitate the widespread adoption of superconducting digital computing.

EDA tools↗
DOE OSTI2014

Concept, implementation and commissioning of the automation system for the accelerator module test facility AMTF

The European XFEL project launched on June 5, 2007 will require about 103 accelerator modules as a main part of the XFEL linear accelerator. All superconducting components constituting the accelerator module like cavities and magnets have to be tested before the assembly. For the tests of the individual cavities and the complete modules an XFEL Accelerator Module Test Facility (AMTF) has been erected at DESY. The process control system EPICS (Experimental Physics and Industrial Control System) is used to control and operate the cryogenic plant and all its subcomponents. A complementary component of EPICS is the Open Source software suit CSS (Control System Studio). CSS is an integrated engineering, maintenance and operating tool for EPICS. CSS enables local and remote operating and monitoring of the complete system and thus represents the human machine interface. More than 250 PROFIBUS nodes work at the accelerator module test facility. DESY installed an extensive diagnostic and condition monitoring system. With these diagnostic tools it is possible to examine the correct installation and configuration of all PROFIBUS nodes in real time. The condition monitoring system based on FDT/DTM technology shows the state of the PROFIBUS devices at a glance. This information can be used for preventive maintenance which is mandatory for continuous operation of the AMTF facility. The poster will describe all steps form engineering to implementation and commissioning.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Production and Fuel properties of Iso-Olefins with Controlled Molecular Structure and Obtained from Butene Oligomerization

The ability to control the molecular structure (e.g., degree of branching) of iso-olefins produced from oligomerizing light olefins is a valuable tool for tuning the final compositions of hydrocarbon fuels and targeting specific fuel properties. In this study, we demonstrated that the degree of branching of iso-olefins obtained from butene(s) oligomerization can be controlled by tuning process conditions (i.e., temperature, weight hourly space velocity [WHSV], and nature of butene feedstock) and by choosing the proper catalyst (i.e., Amberlyst-36 vs. Y/ZSM-22). In this study, we produced three types of iso-olefin mixtures: 1) a methyl-heptenes rich (74 wt.%) mixture, 2) dimethyl-hexenes rich (80–96 wt.%) mixtures, and 3) highly branched (i.e., more than three methyl substitutions) iso-olefins rich (>50 wt.%) mixtures. While dimethyl-hexenes are preferentially formed at lower temperatures (60–100°C) and WHSV (i.e., 2 hr-1), methyl-heptenes are favorably produced at higher temperatures (>100°C) and WHSVs (i.e., 7 hr-1) over Amberlyst-36. The use of either 1-butene or 2-butene as feedstock resulted in liquid products with similar branching because facile intramolecular isomerization occurs prior to oligomerization. However, the use of isobutylene feedstock forms a significantly more branched olefin product. The formation of highly branched iso-olefins also is favored at higher temperature (140°C) over Amberlyst-36. Using Y/ZSM-22 instead of Amberlyst-36 allowed preferential formation of less-branched methyl-heptenes. For each type of iso-olefins mixture, we determined fuel properties including research octane number (RON), motor octane number (MON), and octane sensitivity (S), which is the difference between RON and MON. We found that not only RON and MON but also S values increased with the degree of branching of these complex mixtures of iso-olefins. The highest RON of 99.7 and S value of 9.3 were obtained for a mixture of highly branched iso-olefins.

Dagle, Vanessa↗
DOE OSTI2016

SU-F-T-505: A Novel Approach for Sparing Critical Organs at Risk for Cancer Patients Undergoing Radiation Oncology Treatments

Purpose: A major goal of an effective radiation treatment plan is to deliver the maximum dose to the tumor while minimizing radiation exposure to the surrounding normal structures. For example, due to the radiation exposure to neighboring critical structures during prostate cancer treatment, a significant increase in cancer risk was observed for the bladder (77%) and the rectum (105%) over the following decade. Consequently, an effective treatment plan necessitates limiting the exposure to such organs which can best be achieved by physically displacing the organ at-risk. The goal of this study is to present a prototype for an organ re-positioner device designed and fabricated to physically move the rectum away from the path of radiation beam during external beam and brachytherapy treatments. This device affords patient comfort and provides a fully controlled motion to safely relocate the rectum during treatment. Methods: The NiTi shape memory alloy was designed and optimized for manufacturing a rectal re-positioner device through cooling and heating the core alloy for its shaping. This has been achieved through a prototyped custom designed electronic circuit in order to induce the reversible austenitic transformation and was tested rigorously to ensure the integrity of the actuated motion in displacement of the target anatomy. Results: The desirable NiTi shape-setting was configured for easy insertion and based on anatomical constraint. When the final prototype was evaluated, accuracy and precision of the maximum displacement and temperature changes revealed that the device could safely be used within the target anatomy. Conclusion: The organ re-positioner device is a promising tool that can be implemented in clinical setting. It provides a controlled and safe displacement of the delicate organ(s) at risk. The location of the organ being treated could also be identified using conventional onboard imaging devices or MV imaging available on-board most modern clinical accelerators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-471: Improvement of Gamma Knife Treatment Planning Through Tumor Control Probability for Metastatic Brain Tumors

Purpose: The dose–volume histogram (DVH) has been normally accepted as a tool for treatment plan evaluation. However, spatial information is lacking in DVH. As a supplement to the DVH in three-dimensional treatment planning, the differential DVH (DDVH) provides the spatial variation, the size and magnitude of the different dose regions within a region of interest, which can be incorporated into tumor control probability model. This study was to provide a method in evaluating and improving Gamma Knife treatment planning. Methods: 10 patients with brain metastases from different primary tumors including melanoma (#1,#4,#5, #10), breast cancer (#2), prostate cancer (#3) and lung cancer (#6–9) were analyzed. By using Leksell GammaPlan software, two plans were prepared for each patient. Special attention was given to the DDVHs that were different for different plans and were used for a comparison between two plans. Dose distribution inside target and tumor control probability (TCP) based on DDVH were calculated, where cell density and radiobiological parameters were adopted from literature. The plans were compared based on DVH, DDVH and TCP. Results: Using DVH, the coverage and selectivity were the same between plans for 10 patients. DDVH were different between two plans for each patient. The paired t-test showed no significant difference in TCP between the two plans. For brain metastases from melanoma (#1, #4–5), breast cancer (#2) and lung cancer (#6–8), the difference in TCP was less than 5%. But the difference in TCP was about 6.5% for patient #3 with the metastasis from prostate cancer, 10.1% and 178.7% for two patients (#9–10) with metastasis from lung cancer. Conclusion: Although DVH provides average dose–volume information, DDVH provides differential dose– volume information with respect to different regions inside the tumor. TCP provides radiobiological information and adds additional information on improving treatment planning as well as adaptive radiotherapy. Further clinical validation is necessary.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

State elimination for mixed‐integer optimal control of partial differential equations by semigroup theory

Abstract Mixed‐integer optimal control problems governed by partial differential equations (MIPDECOs) are powerful modeling tools but also challenging in terms of theory and computation. We propose a highly efficient state elimination approach for MIPDECOs that are governed by partial differential equations that have the structure of an abstract ordinary differential equation in function space. This allows us to avoid repeated calculations of the states for all time steps, and our approach is applied only once before starting the optimization. The presentation of theoretical results is complemented by numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Anomalous structural recovery in the near glass transition range in a polymer glass: Data revisited in light of temperature variability in vacuum oven‐based experiments*

Abstract There is considerable interest in data reported by Cangialosi et al. [Cangialosi, D., Boucher, V. M., Alegría, A., & Colmenero, J. (2013). Physical Review Letters , 111 (9), 095701] that purportedly showed unusual irregular responses in the isothermal structural recovery behavior of glasses because the observation challenges the general view of the dynamics being smooth functions of time as observed in extensive dilatometric experiments by Kovacs [Kovacs, A. J. (1964). In Fortschritte der Hochpolymeren‐Forschung , 3 , 394–507. Springer, Berlin, Heidelberg.] in the 1960s. The reported data show an apparent two mechanism structural (enthalpy) recovery at aging temperatures ranging from 6 to 17 K below which is also controversial as it could not be reproduced in work from Koh and Simon [Koh, Y. P., & Simon, S. L. (2013). Macromolecules , 46(14), 5815–5821.] where a second plateau observed in the enthalpy loss curve was not reproduced in nearly 1‐year‐long experiments at 15 K below . Therefore, it is important to determine what might be possible reasons for the apparent non‐smooth relaxations. Here, we examine the possibility that the poor temperature control of a typical vacuum oven could explain the anomalous results. We used the Tool–Narayanaswamy–Moynihan (TNM) model of structural recovery to calculate the effect of typical vacuum oven temperature variation on the structural recovery of polystyrene and find that we can reproduce the reported experimental results. The issue of temperature control using a vacuum oven is discussed, and data from thermocouple measurements of temperature at various locations inside a vacuum oven are shown.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Model Validation of the Honda Accord Plug-In

This paper presents the validation of an entire vehicle model of the Honda Accord Plug-in Hybrid Electric Vehicle (PHEV), which has a new powertrain system that can be driven in both series and parallel hybrid drive using a clutch, including thermal aspects. The Accord PHEV is a series-parallel PHEV with about 21 km of all-electric range and no multi-speed gearbox. Vehicle testing was performed at Argonne’s Advanced Powertrain Research Facility on a chassis dynamometer set in a thermal chamber. First, components (engine, battery, motors and wheels) were modeled using the test data and publicly available assumptions. This includes calibration of the thermal aspects, such as engine efficiency as a function of coolant temperature. In the second phase, the vehicle-level control strategy, especially the energy management, was analyzed in normal conditions in both charge-depleting and charge-sustaining modes. The third part examined how different thermal conditions such as environmental conditions (–7°C or 35°C with solar load) or vehicle state (soaked or warmed-up vehicle) affect the control strategy. Finally, the validation of the model implemented in Autonomie, a high-fidelity, forward-looking vehicle simulation tool, is presented. The fuel consumption figures are within the test-to-test variability, while many of the operation and control signals are also matched. Now that it has been validated, this model can be used for a wide range of simulations studies that include temperature as a parameter for the comparison and optimization of components, vehicle powertrain system, or control algorithm.

Jeong, Jongryeol↗
DOE OSTI2025

Covariance-Free Bifidelity Control Variates Importance Sampling for Rare Event Reliability Analysis

Multifidelity modeling has been steadily gaining attention as a tool to address the problem of exorbitant model evaluation costs that makes the estimation of failure probabilities a significant computational challenge for complex real-world problems, particularly when failure is a rare event. To implement multifidelity modeling, estimators that efficiently combine information from multiple models/sources are necessary. In past works, the variance reduction techniques of control variates (CV) and importance sampling (IS) have been leveraged for this task. In this paper, we present the CVIS framework—a creative take on a coupled CV and IS estimator for bifidelity reliability analysis. The framework addresses some of the practical challenges of the CV method by using an estimator for the control variate mean and sidestepping the need to estimate the covariance between the original estimator and the control variate through a clever choice for the tuning constant. Furthermore, the task of selecting an efficient IS distribution is also considered, with a view towards maximally leveraging the bifidelity structure and maintaining expressivity. Additionally, a diagnostic is provided that indicates both the efficiency of the algorithm as well as the relative predictive quality of the models utilized. Finally, the behavior and performance of the framework is explored through analytical and numerical examples.

Markov chain Monte Carlo↗
DOE OSTI2022

Multipolariton control in attosecond transient absorption of autoionizing states

Tunable attosecond transient absorption spectroscopy is an ideal tool for studying and manipulating autoionization dynamics in the continuum. We investigate near-resonant two-photon couplings between the bright 3s –1 4p and dark 3s –1 4f autoionizing states of argon that lead to Autler-Townes-like interactions, forming entangled light-matter states or polaritons. We observe that one-photon couplings with intermediate dark states play an important role in this interaction, leading to the formation of multiple polaritonic branches whose energies exhibit avoided crossings as a function of the dressing-laser frequency. Our experimental measurements and theoretical essential-state simulations show good agreement and reveal how the delay, frequency, and intensity of the dressing pulse govern the properties of autoionizing polariton multiplets. Furthermore, these results demonstrate new pathways for quantum control of autoionizing states with optical fields.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Development and experimental qualification of a calculation scheme for the evaluation of gamma heating in experimental reactors. Application to MARIA and Jules Horowitz (JHR) MTR Reactors

Precise computational determination of nuclear heating which consists predominantly of gamma heating (more than 80 %) is one of the challenges in material testing reactor exploitation. Due to sophisticated construction and conditions of experimental programs planned in JHR it became essential to use most accurate and precise gamma heating model. Before the JHR starts to operate, gamma heating evaluation methods need to be developed and qualified in other experimental reactor facilities. This is done inter alia using OSIRIS, MINERVE or EOLE research reactors in France. Furthermore, MARIA - Polish material testing reactor - has been chosen to contribute to the qualification of gamma heating calculation schemes/tools. This reactor has some characteristics close to those of JHR (beryllium usage, fuel element geometry). To evaluate gamma heating in JHR and MARIA reactors, both simulation tools and experimental program have been developed and performed. For gamma heating simulation, new calculation scheme and gamma heating model of MARIA have been carried out using TRIPOLI4 and APOLLO2 codes. Calculation outcome has been verified by comparison to experimental measurements in MARIA reactor. To have more precise calculation results, model of MARIA in TRIPOLI4 has been made using the whole geometry of the core. This has been done for the first time in the history of MARIA reactor and was complex due to cut cone shape of all its elements. Material composition of burnt fuel elements has been implemented from APOLLO2 calculations. An experiment for nuclear heating measurements and calculation verification has been done in September 2014. This involved neutron, photon and nuclear heating measurements at selected locations in MARIA reactor using in particular Rh SPND, Ag SPND, Ionization Chamber (all three from CEA), KAROLINA calorimeter (NCBJ) and Gamma Thermometer (CEA/SCK CEN). Measurements were done in forty points using four channels. Maximal nuclear heating evaluated from measurements is of the order of 2.5 W/g at half of the possible MARIA power - 15 MW. The approach and the detailed program for experimental verification of calculations will be presented. The following points will be discussed: - Development of a gamma heating model of MARIA reactor with TRIPOLI 4 (coupled neutron-photon mode) and APOLLO2 model taking into account the key parameters like: configuration of the core, experimental loading, control rod location, reactor power, fuel depletion); - Design of specific measurement tools for MARIA experiments including for instance a new single-cell calorimeter called KAROLINA calorimeter; - MARIA experimental program description and a preliminary analysis of results; - Comparison of calculations for JHR and MARIA cores with experimental verification analysis, calculation behavior and n-γ 'environments'. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Machine‐learning‐based predictive control of nonlinear processes. Part II: Computational implementation

Abstract Machine learning is receiving more attention in classical engineering fields, and in particular, recurrent neural networks (RNNs) coupled with ensemble regression tools have demonstrated the capability of modeling nonlinear dynamic processes. In Part I of this two‐article series, the Lyapunov‐based model predictive control (LMPC) method using a single RNN model and an ensemble of RNN models, respectively, was rigorously developed for a general class of nonlinear systems. In the present article, computational implementation issues of this new control method ranging from training of the RNN models, ensemble regression of the RNN models, and parallel computation for accelerating the real‐time model calculations are addressed. Furthermore, a chemical reactor example is used to demonstrate the implementation and effectiveness of these machine‐learning tools in LMPC as well as compare them with standard state‐space model identification tools.

Wu, Zhe↗
DOE OSTI2020

An Update to the NREL Baseline Wind Turbine Controller: Preprint

The NREL 5MW wind turbine model is well established as an industry standard and is often used as a comparison model, or a model on which to build upon. Though effective, the legacy controller for the NREL 5MW wind turbine is built on a simple algorithm that is not up to date with many industry standards. Additionally, as the research community has advanced into more fast-paced development cycles, as systems engineering tools such as WISDEM \cite{WISDEM} are employed, and as a greater focus on controls co-design practices is encouraged, a demand for a generic wind turbine controller has arisen. This work presents updates for the NREL 5MW baseline controller to a more modern control architecture, and establishes a generic tuning framework that can be easily adapted to various wind turbines. Based on initial results, the updated generic controller eases the automatic tuning process, while maintaining or improving upon the performance of the legacy NREL 5MW controller.

17 WIND ENERGY↗
DOE OSTI2020

Closing the Gap Between Modeling and Experiments in the Self-assembly of Biomolecules at Interfaces and in Solution

Molecular self-assembly is a powerful tool in materials design, wherein non-covalent interactions like electrostatic, hydrophobic, hydrogen bonding, and van der Waals can be exploited to produce supramolecular nanostructures that are functional and highly tunable. Biomolecules are attractive building blocks, as they are biocompatible, biodegradable and adopt a wide array of higher order structures. Moreover, naturally occurring protein systems display a manifold of structures and interactions that can be replicated in synthetic biomolecules. In this perspective, we highlight advances in multiscale simulation techniques across broad spatiotemporal scales that can aid in characterizing self-assembly of hybrid and hierarchical bionanomaterial systems, with an emphasis on physics-based simulation approaches currently employed to study biomolecules at mineral interfaces. The power of these approaches is highlighted across a few recent areas where molecular simulations have advanced our understanding of self-assembly spanning peptides to protein self-assembly. Looking forward, we discuss how in the near future emerging methods in statistical and machine learning will advance this research field in all areas from expanding the capabilities of physics-based simulation methods to enabling new analyses of high throughput experiments. These advances will pave the way for understanding the molecular recognition patterns in systems that are dictated by self-assembly - biomineralizing peptides, hierarchical peptoids, and large protein assemblies, and will aid in the development of a new synthesis science for achieving precise molecular control in materials design

Sampath, Janani↗
DOE OSTI2022

A de novo matrix for macroscopic living materials from bacteria

Engineered living materials (ELMs) embed living cells in a biopolymer matrix to create materials with tailored functions. While bottom-up assembly of macroscopic ELMs with a de novo matrix would offer the greatest control over material properties, we lack the ability to genetically encode a protein matrix that leads to collective self-organization. Here we report growth of ELMs from Caulobacter crescentus cells that display and secrete a self-interacting protein. This protein formed a de novo matrix and assembled cells into centimeter-scale ELMs. Discovery of design and assembly principles allowed us to tune the composition, mechanical properties, and catalytic function of these ELMs. This work provides genetic tools, design and assembly rules, and a platform for growing ELMs with control over both matrix and cellular structure and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Automata-based Debugging for Dissimilar Parallel Tasks

AutomaDeD is a tool that automatically diagnoses performance and correctness faults in MPI applications. It creates time and control-flow models of processes in an MPI program, and when a failure occus, these models are analyzed probabilistically to find the origin of the failure. The output of the tool is MPI processes ranked by the abnormality degree and regions of code where faults are first manifested. The granularity of code region is an MPI call or a computation region between two MPI calls.

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