Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Active target experiments”

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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

InSight Robotic Arm Testing Activities for HP3 Mole Anomaly Recovery on Mars

The InSight lander’s Heat Flow and Physical Properties Package (HP3 ) was deployed on Mars in February 2019 and began attempting to penetrate to its target depth range of 3-5 meters shortly thereafter. However, the mole’s downward progress stopped after only 35 cm of penetration. In response, the project convened an Anomaly Response Team (ART) and since then has been attempting to diagnose the problem and assist the mole using the tools available on Mars. The key asset used in this effort has been the Instrument Deployment System (IDS), which includes two cameras and a robotic Instrument Deployment Arm (IDA). Since the IDS was originally intended only to deploy InSight’s primary instruments to the Martian surface, new testbed setups, experiments, and operational protocols (e.g., command sequences) were required and had to be developed on a short timeline. The HP3 Mole ART first focused on gathering all observable data on Mars about the state of the mole and Support Structure Assembly (SSA), as well as the physical properties of the Martian regolith. This included using the robotic arm to point the IDC (Instrument Deployment Camera) at the SSA during diagnostic hammering attempts to observe motion of the SSA and science tether. Images taken during these attempts revealed some motion of the SSA, but no apparent change in mole depth. At JPL, the IDS and Testbed teams re-created the hardware configuration on Mars based on limited knowledge of the mole’s state. They devised and tested techniques to use the robotic arm and cameras to accomplish previously untested activities on Mars, including imaging the HP3 , using the IDA to interact with the terrain, and using the IDA to move the SSA away from the partially-embedded mole. The team executed the more promising techniques on Mars. After diagnostic hammering on Mars, the team decided to move the SSA to gain visibility of the mole’s configuration and access to the soil around the mole. After developing the technique and practicing the maneuver in the InSight testbed, the team lifted the SSA on Mars and placed it behind the mole. This revealed a pit surrounding the now exposed mole, observations of which provided essential clues for determining the root cause of the mole’s lack of progress. The IDS and Testbed teams altered the testbed to match the situation on Mars. They devised IDA techniques to determine the Martian soil properties and assist the mole’s descent. They tested these techniques in the testbed and executed the more promising ones on Mars. These include using the robotic arm to alter the regolith near the mole and to push on the mole while it hammers. This paper discusses the anomaly resolution testing in the testbed at JPL, describes how the IDS team prepared for the anomaly recovery activities on Mars, and provides preliminary results of the efforts to assist the HP3 mole on Mars.

Kim, Junggon↗
DOE OSTI2021

LncRNA DLEU2 promotes cervical cancer cell proliferation by regulating cell cycle and NOTCH pathway

Highlights: • LncRNA DLEU2 is upregulated and related to tumor topography in cervical cancer. • LncRNA DLEU2 promotes cervical cancer cell proliferation. • LncRNA DLEU2 promotes the progression of the cell cycle. • LncRNA DLEU2 inhibits the activity of the Notch signaling pathway. Long noncoding RNAs (lncRNAs) are known to play a crucial role in the onset and progression of cervical cancer (CC). Here, the results of RNA microarray and RNA-sequencing dataset analysis showed that lncRNA DLEU2 was significantly upregulated in CC tissues. Clinicopathologic analysis indicated that lncRNA DLEU2 was closely related to tumor topography. Functional experiments and bioinformatics analysis revealed that lncRNA DLEU2 promoted CC cell proliferation and accelerated the cell cycle. Mechanistically, lncRNA DLEU2 promoted the progression of the cell cycle and inhibited the activity of the Notch signaling pathway by inhibiting p53 expression. Additionally, lncRNA DLEU2 probably interacted with ZFP36 Ring Finger Protein (ZFP36) to inhibit the expression of p53. In conclusion, this study revealed the function of lncRNA DLEU2 in CC tumorigenesis, suggesting new therapeutic targets in CC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Site-Differentiated Iron–Sulfur Cluster Ligation Affects Flavin-Based Electron Bifurcation Activity

Electron bifurcation is an elegant mechanism of biological energy conversion that effectively couples three different physiologically relevant substrates. As such, enzymes that perform this function often play critical roles in modulating cellular redox metabolism. One such enzyme is NADH-dependent reduced-ferredoxin: NADP+ oxidoreductase (NfnSL), which couples the thermodynamically favorable reduction of NAD+ to drive the unfavorable reduction of ferredoxin from NADPH. The interaction of NfnSL with its substrates is constrained to strict stoichiometric conditions, which ensures minimal energy losses from non-productive intramolecular electron transfer reactions. However, the determinants for this are not well understood. One curious feature of NfnSL is that both initial acceptors of bifurcated electrons are unique iron–sulfur (FeS) clusters containing one non-cysteinyl ligand each. The biochemical impact and mechanistic roles of site-differentiated FeS ligands are enigmatic, despite their incidence in many redox active enzymes. Herein, we describe the biochemical study of wild-type NfnSL and a variant in which one of the site-differentiated ligands has been replaced with a cysteine. Results of dye-based steady-state kinetics experiments, substrate-binding measurements, biochemical activity assays, and assessments of electron distribution across the enzyme indicate that this site-differentiated ligand in NfnSL plays a role in maintaining fidelity of the coordinated reactions performed by the two electron transfer pathways. Given the commonality of these cofactors, our findings have broad implications beyond electron bifurcation and mechanistic biochemistry and may inform on means of modulating the redox balance of the cell for targeted metabolic engineering approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

COMET Progresses Toward First Mission

The COMmercial Experiment Transporter (COMET) is a set of hardware and related infrastructure used to support orbital experiments of the CDD's and their industrial partners. During this year major support contracts were signed, preliminary design reviews conducted, experiments selected for the first mission, and long lead items place on order. The Program Office and CCDS Monitors took an active role in guiding COMET through the activation maze. Launch and recovery sites were selected and licenses for the launch vehicle, recovery system, and recovery operations were filed by the contractors with the Department of Transportation. As the period closed, COMET was preparing for Critical Design Reviews on all major systems and a target launch data was selected. This report deals primarily with the programmatic issues which were resolved as the program matured. At times is is impossible to disassociate the technical from the programmatic and, in such cases the technical material is presented to provide insight into the paths selected by both CCDS and Contractor Management.

Pawlick, J.↗
NASA NTRS2016

A Computationally-Efficient, Multi-Mechanism Based Framework for the Comprehensive Modeling of the Evolutionary Behavior of Shape Memory Alloys

The report summarizes the accomplishments made during the 4-year duration of the project. Here, the major emphasis is placed on the different tasks performed by the two research teams; i.e., the modeling activities by the University of Akron (UA) team and the experimental and neutron diffraction studies conducted by the University of Central Florida (UCF) team, during this 4-year period. Further technical details are given in the upcoming sections by UA and UCF for each of the milestones/years (together with the corresponding figures and captions).The project majorly involved the development, validation, and application of a general theoretical model that is capable of capturing the nonlinear hysteretic responses, including pseudoelasticity, shape memory effect, rate-dependency, multi-axiality, asymmetry in tension versus compression response of shape memory alloys. Among the targeted goals for the SMA model was its ability to account for the evolutionary character response (including transient and long term behavior under sustained cycles) for both conventional and high temperature (HT) SMAs, as well as being able to simulate some of the devices which exploit these unique material systems. This required extensive (uniaxial and multi-axial) experiments needed to guide us in calibrating and characterizing the model. Moreover, since the model is formulated on the theoretical notion of internal state variables (ISVs), neutron diffraction experiments were needed to establish the linkage between the micromechanical changes and these ISVs. In addition, the design of the model should allow easy implementation in large scale finite element application to study the behavior of devices making use of these SMA materials under different loading controls. Summary of the activities, progress/achievements made during this period is given below in details for the University of Akron and the University (Section 2.0) of Central Florida (Section 3.0).

Alloys↗
DOE OSTI2022

A process optimization framework for laser direct energy deposition: Densification, microstructure, and mechanical properties of an Fe-Cr alloy

Laser Direct Energy Deposition (DED) is a metal additive manufacturing technique with the ability to fabricate large and complex parts through deposition of metal powders. However, achieving high-density parts and targeted build heights using DED can be challenging due to the large number of highly sensitive process variables. This work proposes a robust fabrication parameter optimization framework to generate process maps for primary parameters in DED, including laser power, scan speed, mass flow rate, hatch spacing, and layer height. Simple single-track experiments were utilized to map out the parameter space, and a combination of geometric criteria for hatch spacing and layer height were proposed to determine parameter sets that achieve both targeted build heights and mitigate porosity formation. Using this framework, specimens with >99 % density and consistent mechanical properties were successfully fabricated over a wide range of process parameters for an Fe-9wt.%Cr (Fe9Cr) alloy, a surrogate for radiation damage-resistant reduced activation ferritic/martensitic (RAFM) steels. Processing these materials using DED is of particular interest in the development of plasma facing components for nuclear fusion applications. The microstructure and mechanical properties of as-printed Fe9Cr were characterized using optical and electron microscopy, X-ray diffraction, and uniaxial tensile tests. As-printed Fe9Cr displayed ~25 % elongation and ultimate tensile strengths of up to 475 MPa which is comparable to similar wrought alloys. Finally, the proposed framework will allow for accelerated DED parameter optimization for novel alloy systems, as well as open the possibility for local microstructure control while simultaneously mitigating defect formation.

42 ENGINEERING↗
NASA NTRS2000

Biocybernetic Control of Vigilance Task Parameters

The major focus of the present proposal was to examine psychophysiological variables that are related to hazardous states of awareness induced by monitoring automated systems. With the increased use of automation in today's work environment, people's roles in the work place are being redefined from that of active participant to one of passive monitor. Although the introduction of automated systems has a number of benefits, there are also a number of disadvantages regarding the worker performance. Byrne and Parasuraman (1996) have argued for the use of psychophysiological measures in both the development and the implementation of adaptive automation. While both performance based and model based adaptive automation have been studied, the use of psychophysiological measures, especially EEG, offers the advantage of real time evaluation of the state of the subject. Previous investigations of the closed-loop adaptive automation system in our laboratory, supported by NASA, have employed a compensatory tracking task which involved the use of a joystick to maintain the position of a cursor in the middle of a video screen. This research demonstrated that, in an adaptive automation, closed-loop environment, subjects perform a tracking task better under a negative, compared to a positive, feedback condition. While tracking is comparable to some aspects of flying an airplane, it does not simulate the environment found in the cockpit of modern commercial airplanes. Since a large part of the flying responsibilities in commercial airplanes is automated, the primary responsibility of pilots is to monitor the automation and to respond when the automation fails. Because failures are relatively rare, pilots often suffer from hazardous states of awareness induced by long term vigilance of the automated system. Consequently, the aim of the current study was to investigate the ability of the closed-loop, adaptive automation system in a vigilance paradigm. It is also important to note that tracking involves a continuous, though low level, motor response. Since it is not clear how such activity might affect performance of the adaptive automation system, it was thought to be important to evaluate how the system functioned when there was minimal motor output by the subjects. The current study used the closed-loop system, developed at NASA-Langley Research Center, to control the state of awareness of subjects while they performed a vigilance task. Several experiments were conducted to examine the use of EEG feedback to control a target dimension used in the task. Changes in a subject's arousal, as defined by specific EEG indexes, produced stimulus changes known to affect task performance. In addition, different electrode sites, compared to previous research, were sampled to determine the optimum configuration with regard to the following criteria: (1) task performance and (2) EEG index.

Freeman, Frederick G.↗
NASA NTRS1989

Integrating automated support for a software management cycle into the TAME system

Software managers are interested in the quantitative management of software quality, cost and progress. An integrated software management methodology, which can be applied throughout the software life cycle for any number purposes, is required. The TAME (Tailoring A Measurement Environment) methodology is based on the improvement paradigm and the goal/question/metric (GQM) paradigm. This methodology helps generate a software engineering process and measurement environment based on the project characteristics. The SQMAR (software quality measurement and assurance technology) is a software quality metric system and methodology applied to the development processes. It is based on the feed forward control principle. Quality target setting is carried out before the plan-do-check-action activities are performed. These methodologies are integrated to realize goal oriented measurement, process control and visual management. A metric setting procedure based on the GQM paradigm, a management system called the software management cycle (SMC), and its application to a case study based on NASA/SEL data are discussed. The expected effects of SMC are quality improvement, managerial cost reduction, accumulation and reuse of experience, and a highly visual management reporting system.

Sunazuka, Toshihiko↗
NASA NTRS2003

Subcellular targeting of nine calcium-dependent protein kinase isoforms from Arabidopsis

Calcium-dependent protein kinases (CDPKs) are specific to plants and some protists. Their activation by calcium makes them important switches for the transduction of intracellular calcium signals. Here, we identify the subcellular targeting potentials for nine CDPK isoforms from Arabidopsis, as determined by expression of green fluorescent protein (GFP) fusions in transgenic plants. Subcellular locations were determined by fluorescence microscopy in cells near the root tip. Isoforms AtCPK3-GFP and AtCPK4-GFP showed a nuclear and cytosolic distribution similar to that of free GFP. Membrane fractionation experiments confirmed that these isoforms were primarily soluble. A membrane association was observed for AtCPKs 1, 7, 8, 9, 16, 21, and 28, based on imaging and membrane fractionation experiments. This correlates with the presence of potential N-terminal acylation sites, consistent with acylation as an important factor in membrane association. All but one of the membrane-associated isoforms targeted exclusively to the plasma membrane. The exception was AtCPK1-GFP, which targeted to peroxisomes, as determined by covisualization with a peroxisome marker. Peroxisome targeting of AtCPK1-GFP was disrupted by a deletion of two potential N-terminal acylation sites. The observation of a peroxisome-located CDPK suggests a mechanism for calcium regulation of peroxisomal functions involved in oxidative stress and lipid metabolism.

Non-NASA Center↗
DOE OSTI2021

Studies on the scintillation light detection in the ProtoDUNE Dual Phase liquid-argon TPC and its capability for the supernova trigger in DUNE

The Deep Underground Neutrino Experiment (DUNE) is a long-baseline neutrino oscillation experiment that aims at addressing key questions in neutrino physics in the next decades. Its scientific program includes the detection of the neutrino flux from a core-collapse supernova. The DUNE far detector will have four 17-kt mass liquid-argon (LAr) time-projection chamber (TPC) modules. ProtoDUNE Dual Phase (DP), a dual-phase LAr TPC with 300 t of active mass and 6 m of drift distance, was operated with cosmic muons in 2019-2020 as part of an R&D program at the CERN Neutrino Platform to demonstrate the feasibility of the technology at such a large scale. In a LAr TPC, the photon detection system (PDS) provides fundamental timing information and trigger capabilities. The PDS of ProtoDUNE-DP, which consisted of 36 photomultiplier tubes (PMTs), counted on a dedicated light calibration system (LCS) to monitor the PMT response. In this dissertation, the characterization and validation of the ProtoDUNE-DP PDS and LCS components before their installation will be reviewed, highlighting the results of general interest for experiments that use liquid noble gasses as target medium. The results from the stable performance of both systems in the detector during 15 months will be presented next as well as the studies on the scintillation light detection in ProtoDUNE-DP, where the collection of light produced in LAr at 7 m from the photosensors has been achieved for the first time. It is worth pointing out that the excellent LAr purity and the large size of the detector have enabled to develop a unique data-driven investigation on aspects that are critical for LAr-based experiments but that are not completely understood. The analyses cover the characterization of the low-energy background detected by the PDS, the quantification of the electric field impact on the light yield, the evaluation of the Rayleigh scattering affecting the light propagation, and the analysis of the PMT detection efficiency. The effect of the VUV reflectivity of the detector materials will be also discussed. In addition, the estimation of the cosmic muon flux crossing the TPC and the study of the observed light yield by the PDS will be reported. Finally, the results from the simulation-based study of the supernova burst trigger capability with the PDS of a 12.1-kt active mass dual-phase LAr TPC as the one proposed for DUNE will be summarized. Several configurations of reflective foils installed in the TPC to enhance the light collection will be compared.

Gallego Ros, Ana↗
DOE OSTI2021

Studies on the scintillation light detection in the ProtoDUNE Dual Phase liquid-argon TPC and its capability for the supernova trigger in DUNE

The Deep Underground Neutrino Experiment (DUNE) is a long-baseline neutrino oscillation experiment that aims at addressing key questions in neutrino physics in the next decades. Its scientific program includes the detection of the neutrino flux from a core-collapse supernova. The DUNE far detector will have four 17-kt mass liquid-argon (LAr) time-projection chamber (TPC) modules. ProtoDUNE Dual Phase (DP), a dual-phase LAr TPC with 300 t of active mass and 6 m of drift distance, was operated with cosmic muons in 2019-2020 as part of an R&D program at the CERN Neutrino Platform to demonstrate the feasibility of the technology at such a large scale. In a LAr TPC, the photon detection system (PDS) provides fun- damental timing information and trigger capabilities. The PDS of ProtoDUNE-DP, which consisted of 36 photomultiplier tubes (PMTs), counted on a dedicated light calibration system (LCS) to monitor the PMT response. In this dissertation, the characterization and validation of the ProtoDUNE-DP PDS and LCS components before their installation will be reviewed, highlighting the results of general interest for experiments that use liquid noble gasses as target medium. The results from the stable performance of both systems in the detector during 15 months will be presented next as well as the studies on the scintillation light detection in ProtoDUNE-DP, where the collection of light produced in LAr at 7 m from the photosensors has been achieved for the first time. It is worth pointing out that the excellent LAr purity and the large size of the detector have enabled to develop a unique data-driven investigation on aspects that are critical for LAr- based experiments but that are not completely understood. The analyses cover the characterization of the low-energy background detected by the PDS, the quantification of the electric field impact on the light yield, the evaluation of the Rayleigh scattering affecting the light propagation, and the analysis of the PMT detection efficiency. The effect of the VUV reflectivity of the detector materials will be also discussed. In addition, the estimation of the cosmic muon flux crossing the TPC and the study of the observed light yield by the PDS will be reported. Finally, the results from the simulation-based study of the supernova burst trigger capability with the PDS of a 12.1-kt active mass dual-phase LAr TPC as the one proposed for DUNE will be summarized. Several configurations of reflective foils installed in the TPC to enhance the light collection will be compared

Gallego-Ros, Ana↗
DOE OSTI2021

A review of machine learning in building load prediction

The surge of machine learning in recent years has been empowering engineer modeling in various fields. The decreasing hardware cost, increasing data accessibility, and advances of building automation system (BAS) allow the collection and storage of a significant amount of building operation data. The two facts provide great opportunities of applying machine learning to building energy systems modeling and analysis. There are a great number of research papers on this topic but there lacks a comprehensive and general review to summarize the current development, limitations, gaps and future trend. In this review paper series, machine learning techniques in building energy system modeling and analysis are reviewed under the organization and logic of the machine learning definition by Tom M. Mitchell: a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. This paper is the first part of the review paper series, which focuses on building load prediction. First, the applications of building load prediction model (task T) are reviewed. Then, the modeling algorithms improving machine learning performance and accuracy (performance P) are reviewed. At the same time, the literature on the data perspective for modeling (experience E), including data engineering from sensors level to data level, pre-processing, feature extraction and selection, is reviewed. Finally, what is well-studied and what is lacking but with great potential are concluded; the gaps between present and future utilization of machine learning techniques are identified; the future trend and development are also predicted. The target readers of this paper are not only researchers from the building side who can get exposed to cutting edge machine learning tools, but also those from machine learning side who can understand the potential and challenge to apply machine learning in buildings.

Liang, Zhang↗
DOE OSTI2020

Crystallography of Reactive Intermediates

Metal–ligand (M–L) multiply bonded complexes hold a central place in inorganic chemistry and catalysis: From fundamental and historical perspectives, these species have played a critical role in the articulation of important bonding principles (i.e. the vanadyl ion in the development of molecular orbital theory); from a practical perspective, these species are critical intermediates in a variety of chemical reactions (i.e. N 2 and O 2 reduction, H 2 O oxidation, and C–H functionalization). For many high-valent, early metal complexes, overlap of ligand-based electrons with vacant π-symmetry orbitals leads to strong M–L multiple bonds. The stability of these species enables straightforward characterization with a suite of standard spectroscopic and diffraction-based experiments. Mid- and late-transition metal complexes, with attendant higher d-electron counts, often support more reactive M–L multiply bonded fragments. The reactivity of these species simultaneously renders them attractive intermediates for catalysis but challenging synthetic targets to observe and characterize. A number of important strategies have been advanced to enable experimental characterization of mid- to late-metal–ligand multiply bonded species. Synthetic manipulation of the coordination geometry and ligand donicity, as well as introduction of sterically encumbering ligands, have each emerged as powerful methods to tame the inherent reactivity of kinetically labile M–L multiple bonds. While these efforts have resulted in families of well-characterized complexes and provided critical insights regarding structure and bonding, the synthetic derivatization required to stabilize M–L fragments of interest often obviates the substrate functionalization activity relevant to catalysis. Photochemical synthesis of reactive species provides a conceptually attractive strategy to generate reactive M–L fragments under conditions compatible with time-resolved or cryogenic steady-state characterization, and photogeneration has enabled observation of a number of reactive M–L fragments. The suite of tools available to characterize photogenerated reactive species is often more limited than typical for kinetically stabilized complexes and structural characterization is typically not possible. Recently, photocrystallographic experiments, in which reactive M–L multiply bonded intermediates are generated within single-crystal matrices, have been advanced as a strategy to interrogate the structures of reactive intermediates in C–H functionalization. Lastly, this Comment describes the historical antecedents to these experiments, highlights examples of photocrystallographic characterization of reactive intermediates, and discusses future opportunities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1998

Analysis of the pre-flight and post-flight calibration procedures performed on the Liulin space radiation dosimeter

Liulin, a dosimetry-radiometry system, was developed to satisfy the requirements for active flux and dose rate measurements for the flight of the second Bulgarian cosmonaut in 1988. The system consists of a compact battery-operated silicon solid state detector unit and a read/write microcomputer and telemetry unit. We describe the pre-flight calibrations with charged particles, using radioactive sources and accelerated 170 MeV/nucleon proton and alpha particles at the Dubna, Russia cyclotron. We discuss comparisons with data obtained on Mir with the French-built tissue equivalent LET spectrometer NAUSICAA. Lastly, we describe post-flight calibrations performed with 1 GeV/nucleon 56Fe ions at the Brookhaven National Laboratory AGS accelerator, where the instrument was mounted in tandem with several thin position-sensitive silicon detectors behind a stopping target. The silicon detectors provided an energy spectrum for the surviving charged nuclear fragments for which the flux and absorbed dose were recorded by Liulin.

long duration↗
DOE OSTI2020

Automation of Active Space Selection for Multireference Methods via Machine Learning on Chemical Bond Dissociation

Predicting and understanding the chemical bond is one of the major challenges of computational quantum chemistry. Kohn–Sham density functional theory (KS-DFT) is the most common method, but approximate density functionals may not be able to describe systems where multiple electronic configurations are equally important. Multiconfigurational wave functions, on the other hand, can provide a detailed understanding of the electronic structures and chemical bonds of such systems. In the complete active space self-consistent field (CASSCF) method, one performs a full configuration interaction calculation in an active space consisting of active electrons and active orbitals. However, CASSCF and its variants require the selection of these active spaces. This choice is not black box; it requires significant experience and testing by the user, and thus active space methods are not considered particularly user-friendly and are employed only by a minority of quantum chemists. Our goal is to popularize these methods by making it easier to make good active space choices. Here, we present a machine learning protocol that performs an automated selection of active spaces for chemical bond dissociation calculations of main group diatomic molecules. The protocol shows high prediction performance for a given target system as long as a properly correlated system is chosen for training. Good active spaces are correctly predicted with a considerably better success rate than random guess (larger than 80% precision for most systems studied). Our automated machine learning protocol shows that a “black-box” mode is possible for facilitating and accelerating the large-scale calculations on multireference systems where single-reference methods such as KS-DFT cannot be applied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Deployment of the HFIRCON transport and depletion tool for plutonium-238 production studies

Irradiation of {sup 237}Np-bearing targets in Oak Ridge National Laboratory's (ORNL) High Flux Isotope Reactor (HFIR) results in the efficient production of {sup 238}Pu, which, in the form of heat source PuO{sub 2}, is used as a reliable power source for deep-space and planetary NASA missions. A technology demonstration subproject was initiated at ORNL in 2011 to develop and implement the technology required to establish a {sup 238}Pu supply chain. A systematic progression of NpO{sub 2}/Al cermet (20 vol.% NpO{sub 2}) activities to date has successfully demonstrated target fabrication, irradiation, and chemical recovery processes. Recent program tasks have included the development of the HFIRCON transport and depletion tool for efficient reactor physics analyses and the evaluation of increased NpO{sub 2} loadings (i.e., beyond 20 vol.%) and NpN-based targets. This paper documents the deployment of the HFIRCON code to assess various Np concentrations in NpO{sub 2}- and NpN-based targets in HFIR's inner small vertical experiment facilities. Results indicate that {sup 238}Pu production and quality can be enhanced with increased Np loadings; however, target conversion rates are reduced. The results recorded in this paper, thermal and material balance evaluations, and testing requirement planning will be used to determine whether increased NpO{sub 2} loadings or NpN-based targets will be further considered. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

STITCHES: creating new scenarios of climate model output by stitching together pieces of existing simulations

Abstract. Climate model output emulation has long been attempted to support impact research, mainly to fill in gaps in the scenario space. Given the computational cost of running coupled earth system models (ESMs), which are usually the domain of supercomputers and require on the order of days to weeks to complete a century-long simulation, only a handful of different scenarios are usually chosen to externally force ESM simulations. An effective emulator, able to run on standard computers in times of the order of minutes rather than days could therefore be used to derive climate information under scenarios that were not run by ESMs. Lately, the necessity of accounting for internal variability has also made the availability of initial-condition ensembles, under a specific scenario, important, further increasing the computational demand. At least so far, emulators have been limited to simplified ESM-like output, either seasonal, annual, or decadal averages of basic quantities, like temperature and precipitation, often emulated independently of one another. With this work, we propose a more comprehensive solution to ESM output emulation. Our emulator, STITCHES, uses existing archives of earth system models' (ESMs) scenario experiments to construct ESM-like output under new scenarios or enrich existing initial-condition ensembles, which is what other emulators also aim to do. Importantly, however, STITCHES' output has the same characteristics of the ESM output it sets out to emulate: multivariate, spatially resolved, and high frequency, representing both the forced component and the internal variability around it. STITCHES extends the idea of time sampling – according to which climate outcomes are stratified by the global warming level at which they manifest themselves, irrespective of the scenario and time at which they occur – to the construction of a continuous history of ESM-like output over the whole 21st century, consistent with a 21st-century trajectory of global surface air temperature (GSAT) derived from the scenario that has been chosen as the target of the emulation. STITCHES does so by first splitting the target GSAT trajectory into decade-long windows, then matching each window in turn to a decade-long window within an existing model simulation from the available scenario runs according to its proximity to the target in absolute size of the temperature anomaly and its rate of change. A look-up table is therefore created of a sequence of existing experiment–time-window combinations that, when stitched together, create a GSAT trajectory “similar” to the target. Importantly, we can then stitch together much more than GSAT from these windows, i.e., any output that the ESM has saved for these existing experiment–time-window combinations, at any frequency and spatial scale available in its archive. We show that the stitching does not introduce artifacts in the great majority of cases (we look at temperature and precipitation at monthly frequency and on the native grid of the ESM and at an index of ENSO activity, the Southern Oscillation Index). This is true even if the criteria for the identification of the decades to be stitched together are chosen to work for a smoothed time series of annual GSAT, a result we expect given the larger amount of noise affecting most other variables at finer spatial scales and higher frequencies, which therefore are more “forgiving” of the stitching. We successfully test the method's performance over many ESMs and scenarios. Only a few exceptions surface, but these less-than-optimal outcomes are always associated with a scarcity of the archived simulations from which we can gather the decade-long windows that form the building blocks of the emulated time series. In the great majority of cases, STITCHES' performance is satisfactory according to metrics that reward consistency in trends, interannual and inter-ensemble variance, and autocorrelation structure of the time series stitched together. The method therefore can be used to create ESM-like output according to new scenarios, on the basis of a trajectory of GSAT produced according to that scenario, which could be easily obtained by a simple climate model. It can also be used to increase the size of existing initial-condition ensembles. There are aspects of our emulator that will immediately disqualify it for specific applications, like when climate information is needed whose characteristics result from accumulated quantities over windows of times longer than those used as pieces by STITCHES, droughts longer than a decade for example. But for many applications, we argue that a stitched product can satisfy the climate information needs of impact researchers. STITCHES cannot emulate ESM output from scenarios that result in GSAT trajectories outside of the envelope available in the archive, nor can it emulate trajectories with shapes different from existing ones (overshoots with negative derivative, for example). Therefore, the size and characteristics of the available archives of ESM output are the principal limitations for STITCHES' deployment. Thus, we argue for the possibility of designing scenario experiments within, for example, the next phase of the Coupled Model Intercomparison Project according to new principles, relieved of the need to produce a number of similar trajectories that vary only in radiative forcing strength but more strategically covering the space of temperature anomalies and rates of change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

The effects of fixation and restricted visual field on vection-induced motion sickness

Approximately 60 percent of healthy human subjects experience motion sickness when exposed to a rotating optokinetic drum. Here, the effects of certain visual factors on susceptibility to motion sickness were determined. Vection data (illusory self-motion), horizontal eye movement recordings, subjective motion sickness report, and a measure of gastric myoelectric activity were obtained from 45 subjects, who were randomly divided into the following three groups: a control group that observed the entire visual field with no fixation, a group that fixated on a central target, and a third group that had a visual field restricted to 15 deg. The experimental session was divided into three 12-min periods: baseline, drum rotation, and recovery. The results showed that fixation greatly reduced nystagmus and slightly reduced vection. The restricted visual field slightly reduced nystagmus and greatly reduced vection. Both of these manipulations significantly reduced symptoms of motion sickness and abnormal gastric myoelectric activity.

Stern, Robert M.↗