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NASA NTRS2024

Expanding Ketamine Application for Treatment of Acute Suicidality in Long-Duration Spaceflight

Introduction. The transition to exploration missions places a heightened risk on behavioral health in spaceflight. Although serious psychiatric emergencies during spaceflight have been rare, longer duration missions increase the possibility of emergence in latent mental health disorders due to genetic predisposition, increased autonomy, isolation, helplessness, loss of family member, or catastrophic events. Complicated grief and bereavement have the highest rate of suicidal ideation. Recently, ketamine has been used as an emergent intervention for acute suicidality, promoting its stability, ease of administration, favorable safety profile, and outcomes for reduction of suicidal intent. The goal of this study was to review current literature and collate the understanding of ketamine as a safe, effective pharmacological adjunct for acute suicidality in spaceflight. Methods. This literature review was conducted to collate data on ketamine use for acute suicidality and inform on stability, limitations and utilization of ketamine within extreme environments. Results. 122 publications were reviewed for relevance including 23 randomized-control trials for ketamine use in behavioral emergencies. Discussion. Ketamine is a diverse pharmaceutical with multiple advantageous indications, including acute suicidality, pain, and sedation. Terrestrial use of ketamine suggests a rapidly efficacious medication for reduction in acute suicidality. As behavioral stressors expand related to extended missions, contingencies for behavioral emergencies become increasingly important. Although this review is not intended to re-develop current International Space Station (ISS) protocols, it is the first to discuss the benefits of ketamine in spaceflight as a potential safe, effective multifaceted tool for future exploration missions and treatment for acute suicidal ideation.

Ketamine, Suicidality, Spaceflight↗

DOE OSTI2021

An evaluation of prognostic factors, oncologic outcomes, and management for primary and recurrent squamous cell carcinoma of the vulva

Objective: To evaluate prognostic factors, outcomes, and management patterns of patients treated for squamous cell carcinoma of the vulva. Methods: One hundred sixty-four women were retrospectively identified with primary squamous cell carcinoma of the vulva treated at our institution between 1/1996–12/2018. Descriptive statistics were performed on patient, tumor, and treatment characteristics. The χ 2 tests and t-tests were used to compare categorical variables and continuous variables, respectively. Recurrence free survival (RFS), overall survival (OS), and disease-specific survival (DSS) were analyzed with Kaplan-Meier estimates, the log-rank test, and Cox proportional hazards. Results: Median follow-up was 52.5 months. Five-year RFS was 67.9%, 60.0%, 42.1%, and 20.0% for stage I–IV, respectively. Five-year DSS was 86.2%, 81.6%, 65.0%, and 42.9% for stage I–IV, respectively. On multivariate analysis, positive margins predicted overall RFS (hazard ratio [HR]=3.55; 95% confidence interval [CI]=1.18–10.73; p=0.025), while presence of lichen sclerosus on pathology (HR=2.78; 95% CI=1.30–5.91; p=0.008) predicted local RFS. OS was predicted by nodal involvement (HR=2.51; 95% CI=1.02–6.13; p=0.043) and positive margins (HR=5.19; 95% CI=2.03–13.26; p=0.001). Adjuvant radiotherapy significantly improved RFS (p=0.016) and DSS (p=0.012) in node-positive patients. Median survival after treatment of local, groin, and pelvic/distant recurrence was 52, 8, and 5 months, respectively. Conclusion: For primary treatment, more conservative surgical approaches can be considered with escalation of treatment in patients with concurrent precursor lesions, positive margins, and/or nodal involvement. Further studies are warranted to improve risk stratification in order to optimize treatment paradigms for vulvar cancer patients.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Developing and Demonstrating a Lab Method for Quantifying Hair Exposure to Environmental Tobacco Smoke with a Forensic Perspective

Forensic science and chemistry curricula often lack hands-on experimental designs that effectively simulate the impact of environmental tobacco smoke (ETS) or other common elements found at crime scenes, such as marijuana, on trace forensic evidence. Hair, a critical form of trace evidence, offers unique advantages for assessing long-term exposure to environmental pollutants, including ETS. This study presents a novel, noninvasive forensic laboratory module designed to evaluate ETS exposure on various human hair types (untreated, dyed, and bleached). The experimental procedure involved controlled cigarette smoke exposure, followed by analysis using UV−visible spectroscopy, FTIR spectroscopy, and zeta potential measurements. Thirteen students participated in the three-week lab module (three sessions per week). Pre- and postlab assessments were conducted to evaluate learning outcomes. The prelab assessment focused on baseline knowledge of forensic hair analysis, as well as student expectations and confidence. The postlab assessment evaluated knowledge gained, technical insights, application of techniques, self-reflection, conceptual understanding, and practical skill development. This design helped students comprehend the effects of chemical treatments that significantly influence hair’s capacity to adsorb ETS residues by altering its physical and chemical properties. Integration of this experiment into the forensic chemistry curriculum led to measurable gains in student understanding, technical competency, and appreciation for realworld forensic applications. This method offers a valuable teaching and investigative tool for assessing individual ETS exposure in forensic contexts.

FTIR↗

DOE OSTI2021

PREPARATION OF CLAY-COATED GLASS SURFACES FOR MICROFLUIDICS-BASED STUDY ON CLAY-FLUID INTERACTIONS

Unique characteristics of clay, even though make any clay abundant shales a good source of adsorbed gas, make them equally difficult to produce. The clay-water interaction can cause significant swelling and fines migration in the shale formation, both of which can significantly impair the overall hydrocarbon recovery from shale. Geomaterial micromodels, developed by functionalizing traditional glass or PDMS surface with geomaterials (e.g., calcite, quartz, clay) can represent the physico-chemical properties of the natural porous media and have been used during the last few years to understand and evaluate the solid-fluid physicochemical interactions. This study focuses on developing a clay-coated geomaterial surface and investigates the effect of base fluid's salinity on clay adsorption to the glass surface. Glass capillary tubes and straight channel borosilicate glass micromodels are coated with Illite clay minerals to represent the pore-scale clay chemistry of Caney Shale, a Mississippian unconventional play in Southern Oklahoma, USA. 10 wt.% of Illite clay slurries made with brines of four different salinities are used to coat the glass-capillary tubes to understand the effect of salinity in clay adsorption on the glass surface and overall coating quality. To achieve a stable coating and evaluate the impact of heat treatment on coating's stability, straight channel glass flow cells coated with Illite clay are heat-treated at low (25 °C) and high temperature (125 °C). Dynamic flooding tests were carried out with brines on the coated surface to evaluate the stability of the coating. The experiments' outcome indicated a strong relationship between the brine's salinity and the adsorption of clay particles on the glass surface. An increase in brine concentration resulted in improved adsorption of clay particles on the glass surface. Experiments involving heat treating the glass surface following the coating demonstrated significant improvement in the stability of the coating.

02 PETROLEUM↗

DOE OSTI2026

Project Development of an Electrochemical Denitration and Caustic Generation System for HLW Pretreatment at Hanford - 26350

An engineering-scale electrochemical processing skid is proposed to perform the denitration of Hanford tank waste, which would help to mitigate a key process concern with the direct feed processing of the Hanford Tank Waste Treatment and Immobilization Plant (WTP). The reduction of nitrates and organic compounds in the waste feed will directly reduce hazardous NOx and ammonia gases generated during the vitrification process, which in turn will aid in addressing potential regulatory and safety challenges associated with processing large volumes of tank waste. This paper highlights the past legacy work, project layout, accomplishments from Phase 1 and research and development envisioned for Phase 2. An innovative electrochemical denitration and caustic generation (EDCGe) process was demonstrated for the pretreatment of tank waste at the Savannah River Site (SRS) in the early 2000s. The denitration electrolyzer, off-gas abatement system, and caustic generator electrolyzer are being developed with the intent that the denitration electrolyzer will convert nitrate and nitrite anions to nitrogen gas while also yielding other gaseous byproducts, which may include N2O, NH3, VOCs, and H2. The gaseous byproducts will be managed via a tandem off-gas catalyst-bed treatment system. The caustic generation electrolyzer will recycle NaOH from the feed to produce a clean caustic stream for use within the batching tanks at Hanford, aiding in the preparation of waste for WTP. The reduction in hazardous emissions and improved waste treatment processes provides a robust solution for nuclear waste management, contributing to environmental safety and regulatory compliance. The EDCGe technology is being adapted, modified, and updated for the preparation of the Direct Feed-High Level Waste (DF-HLW) flowsheet at Hanford. Phase 1 demonstrated a bench-scale proof-of-concept for reactions involving the denitration electrolyzer and gas phase abatement of ammonia. The electrochemical technology is drawing on the scientific outcomes that were reported in the legacy work. The results from Phase 1 demonstrated the viability of the EDCGe system in reducing the nitrogen species of simple non-radioactive waste simulants. Commercially available alloys used as electrode materials and membranes are being studied for the denitration and caustic generation electrolyzers. The continuation of this project holds promise for broader applications, such as energy-efficient ammonia production, and contributes significant advancements in nuclear waste management. Additional material discovery has been investigated into ceramic Na super ion conductive (NaSICON) materials and off-gas abatement catalyst discovery. NaSICON is of interest for selective transport of Na within the electrolyzers to make a clean caustic stream. Future integration and optimization efforts, informed by Phase 1 results and ongoing research, will continue to drive advancements in nuclear waste management technology. The technology developed for the EDCGe treatment of tank waste will also have broader potential to inform other fields, such as energy-efficient ammonia production, as well as ammonia abatement catalysis through the lessons learned in electrochemical nitrate reduction. The applications and benefits of this research extend beyond Hanford and the Savannah River Site, supported by a collaborative team of scientists and engineers from national labs, academia, and industry, ensuring a comprehensive approach to solving complex waste treatment challenges. The team is leveraging advanced electrochemical technologies, machine learning, novel catalysts tailored for gaseous nitrogen species, and cutting-edge reactor systems to enhance the process efficiency and effectiveness of the denitration process.

Rodene, Dylan [Savannah River National Laboratory ↗

DOE OSTI2022

Effect of vaccination on the case fatality rate for COVID-19 infections 2020–2021: multivariate modelling of data from the US Department of Veterans Affairs

Objectives: To evaluate the benefits of vaccination on the case fatality rate (CFR) for COVID-19 infections. Design, setting and participants: The US Department of Veterans Affairs has 130 medical centres. We created multivariate models from these data—339 772 patients with COVID-19—as of 30 September 2021. Outcome measures: The primary outcome for all models was death within 60 days of the diagnosis. Logistic regression was used to derive adjusted ORs for vaccination and infection with Delta versus earlier variants. Models were adjusted for confounding factors, including demographics, comorbidity indices and novel parameters representing prior diagnoses, vital signs/baseline laboratory tests and outpatient treatments. Patients with a Delta infection were divided into eight cohorts based on the time from vaccination to diagnosis. A common model was used to estimate the odds of death associated with vaccination for each cohort relative to that of unvaccinated patients. Results: 9.1% of subjects were vaccinated. 21.5% had the Delta variant. 18 120 patients (5.33%) died within 60 days of their diagnoses. The adjusted OR for a Delta infection was 1.87±0.05, which corresponds to a relative risk (RR) of 1.78. The overall adjusted OR for prior vaccination was 0.280±0.011 corresponding to an RR of 0.291. Raw CFR rose steadily after 10–14 weeks. The OR for vaccination remained stable for 10–34 weeks. Conclusions: Our CFR model controls for the severity of confounding factors and priority of vaccination, rather than solely using the presence of comorbidities. Our results confirm that Delta was more lethal than earlier variants and that vaccination is an effective means of preventing death. After adjusting for major selection biases, we found no evidence that the benefits of vaccination on CFR declined over 34 weeks. We suggest that this model can be used to evaluate vaccines designed for emerging variants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Characterizing the Influence of Organic Polymers on the Specific Reactivity of Particulate Remedial Amendments

Commercially available particulate amendments demonstrate high reactivity for effective treatment of water soluble organic and inorganic contaminants in laboratory studies; however, transport of these particles is constrained in the subsurface. In many field applications, particulate amendments are mixed with organic polymers to enhance mobility for direct push applications or stabilize suspensions for high mass loadings. As such, the interactions between particulate amendments, organic polymers and contaminant species need to be systematically investigated to properly understand mechanistic processes that facilitate predictive performance metrics for specific applications in situ . In this study, batch experiments were conducted to quantify the effects of organic polymers (xanthan gum, guar gum, and sodium alginate), polymer concentration (800 and 4,000 mg/L), and aging (up to 28 days) on chromate treatment rate and capacity by two classes of amendments: reductants [granular zero-valent iron (gZVI), micron-ZVI (mZVI), sulfur modified iron (SMI)], and an adsorbent (bismuth sub-nitrate). When particulate amendments were suspended in polymer solutions, reductants retained between 84–100% of the amendment treatment capacity. Conversely, the adsorbent maintained 63–97% relative treatment capacity of the no-polymer control. Polymer solutions had a more pronounced impact on the rate of chromate removal; first order rates of chemical reduction decreased by as much as 70% and adsorption by up to 81% relative to the no-polymer controls. Polymer–amendment aging experiments also showed decreased Cr(VI) treatment capacity; reductants decreased by as much as 24% and adsorption decreased by as much as 44% after 28 days of incubation. While polymer suspensions are needed to aid the injection of particulate amendments into the subsurface, the results from this study indicate potential losses of treatment capacity and a decrease in the rate of remedial performance due to the physical and chemical interactions between polymer suspensions and reactive particulate amendments. Simple batch systems provide baseline characterization of tripartite interactions for the removal of Cr(VI). Additional work is needed to quantify the full impact of polymers on remedial outcomes under site relevant conditions at field scale.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics↗

DOE OSTI2022

Modulating the Pseudoelastic Response of Nitinol Using Ion Implantation

This work explores whether ion beam modification can be used to modulate the austenite to martensite phase transformation in Nickel-Titanium (NiTi), thereby achieving novel or localized transformation properties in near-surface regions. We report this could provide alternatives to laser shot peening or other surface treatment methods and possibly expand applications in biomedical, aerospace, and other fields. Irradiation induces defects and internal stress that can serve as nucleation and/or pinning sites for the phase transformation. Thus, it can augment more convention- al approaches, including alloying, severe mechanical work, grain size reduction, and precipitation of coherent precipitates. A range of outcomes is possible in principle, including a shift of the critical stress or temperature for onset of the transformation, linearization, reduction of hysteresis, stabilization, and extent of transformation strain.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Tailoring microstructures with mild magnetic-field processing: A case study of CuNiFe alloys

Combined experimental and computational investigations of the CuNiFe spinodal system confirm that application of a mild magnetic field during thermal treatment alters elemental redistribution and the resulting microstructure, relative to that obtained from zero-field annealing. Spinodal decomposition of a Cu 40 Ni 42 Fe 18 alloy was initiated during thermal treatment at 773 K, conducted either under zero field or modest (60 mT) magnetic f ield conditions for up to 200 h. Periodic (~10 nm) chemical modulations into Cu-rich and NiFe-rich regions were observed under both conditions, with the amplitude and wavelength of the segregated regions increasing with treatment time. However, magnetic field annealing resulted in a more than twofold increase in the amplitude of elemental modulations relative to zero-field conditions – consistent with enhanced diffusional f luxes during spinodal decomposition – while the modulation wavelength remained largely unaffected. These microstructural differences are reflected in various extrinsic magnetic properties. In parallel, first-principles DFT calculations indicate that long-range ferromagnetic order, as induced by an applied magnetic field, substantially alters the strength and nature of atomic interactions, enhancing the thermodynamic instability of the CuNiFe solid solution. Collectively, these results suggest that incorporating a mild (millitesla-level) magnetic field – distinct from the strong (tesla-level) fields commonly used in prior studies – during thermal processing has the potential to deliver enhanced control of microstructures for targeted engineering outcomes.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Overview of a Versatile Loading System for Anisotropic Material Property Characterization

Additive manufacturing, cold rolling, and other thermomechanical treatments on metals, especially HCP, can cause texture and oriented grain structures resulting in anisotropic mechanical properties. This can lead to macroscopic response that significantly deviates from isotropic assumptions which motivates studying mechanical properties in multiple directions. In addition, multiaxial loading and complex stress states overlapping the above mentioned material anisotropy can lead to unexpected outcomes. Idaho National Laboratory developed an advanced mechanical testing system to study a range of uniaxial to multiaxial stress states while measuring the anisotropic response bringing insight into the overlap between material properties and stress states. High-temperature capability and stress- or strain-controlled loading is available to enable a variety of experiment types and conditions to measure elastic, plastic, and viscoplastic properties. This poster presents the design and capabilities of this system with preliminary results highlighting the benefits of multiaxial loading and anisotropic analysis in an integrated system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2017

A Probabilistic Asteroid Impact Risk Model

Asteroid threat assessment requires the quantification of both the impact likelihood and resulting consequence across the range of possible events. This paper presents a probabilistic asteroid impact risk (PAIR) assessment model developed for this purpose. The model incorporates published impact frequency rates with state-of-the-art consequence assessment tools, applied within a Monte Carlo framework that generates sets of impact scenarios from uncertain parameter distributions. Explicit treatment of atmospheric entry is included to produce energy deposition rates that account for the effects of thermal ablation and object fragmentation. These energy deposition rates are used to model the resulting ground damage, and affected populations are computed for the sampled impact locations. The results for each scenario are aggregated into a distribution of potential outcomes that reflect the range of uncertain impact parameters, population densities, and strike probabilities. As an illustration of the utility of the PAIR model, the results are used to address the question of what minimum size asteroid constitutes a threat to the population. To answer this question, complete distributions of results are combined with a hypothetical risk tolerance posture to provide the minimum size, given sets of initial assumptions. Model outputs demonstrate how such questions can be answered and provide a means for interpreting the effect that input assumptions and uncertainty can have on final risk-based decisions. Model results can be used to prioritize investments to gain knowledge in critical areas or, conversely, to identify areas where additional data has little effect on the metrics of interest.

Asteroid↗

NASA NTRSDate not supplied

Conclusions of a Mini Technical Interchange Meeting on Mechanisms and Pathways Common Between Adverse Health Outcomes from Exposures to Space Radiation

To enable deep space exploration and sustained human presence in space, the NASA Human Research Program’s (HRP) Space Radiation Element (SRE) funds research to characterize and mitigate adverse health outcomes from exposure to space radiation that include risks of carcinogenesis, cardiovascular disease (CVD) and central nervous system (CNS) decrements. Over the past decade, a growing body of compelling experimental evidence suggests shared mechanisms and pathophysiological processes for CVD, neurodegenerative effects, and cancer development and progression, which are traditionally managed as separate disease processes. Additionally, epidemiological studies have identified cross-sectional and longitudinal associations between some specific types of cancer and CVD, and accumulating evidence indicates that the pathogenesis of neurodegenerative diseases such as Alzheimer’s disease may overlap with CVD and cancer pathogenesis. Identifying the mechanisms and pathways common to these important health decrements will not only accelerate development of effective countermeasures and improve management of spaceflight-induced risk, it will also help to develop new treatment strategies for patients on Earth. To identify common pathways and mechanisms of disease induction and progression from current SR-funded studies and to inform future work and solicitations, the SRE organizes themed sessions at annual HRP Investigators’ Workshops (IWS). These technical interchange meetings (TIMs) provide a venue for the scientific community to present ongoing work and engage in open discussion on results, limitations of current approaches, and incorporation of novel experimental strategies, model systems, and other innovative techniques. Here a summary and lessons learned from the SRE-sponsored mini-TIM titled “mechanisms and pathways common between adverse health outcomes” held at HRP IWS 2023 will be communicated. The 90-min TIM had 30-min dedicated to discussing and developing potential collaboration and tissue sharing opportunities among investigators. The SRE facilitated the discussion using a set of pressing questions and gaps in knowledge that need to be addressed by the scientific community. This poster presents the outcomes of the session along with proposed future workshops and other SRE initiatives.

Janapriya Saha↗

NASA NTRSDate not supplied

Conclusions of a Mini Technical Interchange Meeting on Mechanisms and Pathways Common Between Adverse Health Outcomes from Exposures to Space Radiation

Janapriya Saha↗

DOE OSTI2022

Effectiveness of supervised exercise, home-based exercise, or walk advice strategies on walking performance and muscle endurance in patients with intermittent claudication (SUNFIT trial): a randomized clinical trial

Abstract Aims Supervised exercise is a guideline-recommended treatment in intermittent claudication (IC). Hospital-based supervised exercise programmes (SEPs) are underutilized, while home-based structured exercise programmes (HSEPs) have attracted interest. The results from HSEP in IC are inconsistent and may confer no benefit over walk advice (WA) and be less effective than SEP. The aim of the study was to compare the effectiveness of best medical treatment, including Nordic pole WA alone, or WA + SEP or WA + HSEP for patients with IC. Methods and results This three-armed, multicentre randomized clinical trial enrolled patients with IC; all patients received best medical treatment including walking poles and the advice of regular Nordic pole walking (WA). For HSEP and SEP, additional exercise programmes were provided. The primarily investigated hypothesis was a non-inferiority analysis of SEP vs. HSEP regarding the 6-min walk test (6MWT) maximum distance, with a pre-defined non-inferiority margin of 50 m. Supporting outcomes included muscle endurance tests and the walking impairment questionnaire. Outcomes were assessed at baseline, 3, 6, and 12 months by a blinded evaluator. Altogether 166 patients (mean age 72 years; 59% males) were randomized. In HSEP and SEP, 24 and 26% patients, respectively, were fully exercise adherent. All three groups improved pain-free walking distance over time, but there were no significant intergroup differences. The intergroup 6MWT difference between SEP and HSEP from 0 to 12 months was –11.6 m, 95% confidence interval: –36.4 to 13.0 m (i.e. within the pre-specified non-inferiority margin). Conclusion The HSEP was non-inferior to SEP in patients with IC. There were no significant differences observed between the three groups at 1 year. Registration ClinicialTrials.gov: NCT02341716.

Sandberg, Anna (ORCID:0000000258432784)↗

NASA NTRS2008

The Integrated Medical Model: Statistical Forecasting of Risks to Crew Health and Mission Success

The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions occurred and decrements the pharmaceuticals and supplies required to diagnose and treat these medical conditions. If supplies are depleted, then the medical condition goes untreated, and crew and mission risk increase. The IMM currently models approximately 30 medical conditions. By the end of FY2008, the IMM will be modeling over 100 medical conditions, approximately 60 of which have been recorded to have occurred during short and long space missions.

Fitts, M. A.↗

DOE OSTI2024

Machine learning models of intermittent operation of RO wellhead water treatment for salinity reduction and nitrate removal

Machine learning models were developed for intermittent multi-mode operation of a wellhead reverse osmosis water purification and desalination system to predict salt passage, nitrate passage, and permeate flux. The models, based on long short-term memory (LSTM) recurrent neural network (RNN) architecture, included an attention mechanism to increase model performance in proximity of the regulatory limit for nitrate. Training and testing of the models for the Startup, Production, Shutdown and Flushing operational modes were based on operational data (consisting of 22 process variables per data sample) acquired every 2–5 s over a six-month period. The significant sets of model input attributes for the different operational modes were assessed via Spearman ranking correlation, Self-Organizing Map (SOM) analysis and feed forward feature selection (FFFS). Although the variability of nitrate passage, salt passage and permeate flux was significant over the four operational modes, prediction performance for the three outcomes were with R2 and Average Absolute Relative Error (AARE) of 0.78–0.95 and 2.96–6.16 %, respectively. Model updates post membrane elements replacement demonstrated similar levels of prediction accuracy. The study results suggest that there is merit in exploring the utility of multi-mode models for sensor fault detection, data imputation, and for potential use in model-predictive control.

Intermittent RO operation↗

DOE OSTI2020

Uniaxial compression of [001]-oriented CaFe 2 As 2 single crystals:the effects of microstructure and temperature on superelasticity Part I: Experimental observations

Micropillar compression experiments on [001]-oriented CaFe 2 As 2 single crystals have recently revealed the existence of superelasticity with a remarkably high elastic limit of over 10%. The collapsed tetragonal phase transition, which is a uni-axial contraction process in which As-As bonds are formed across an intervening Ca-plane, is the main mechanism of superelasticity. Usually, superelasticity and the related structural transitions are affected strongly by both the microstructure and the temperature. As such, in this study, we investigated how the microstructure and temperature affect the superelasticity of [001]-oriented CaFe 2 As 2 micropillars cut from solution-grown single crystals, by performing a combination of in-situ cryogenic micromechanical testing and transmission electron microscopy studies. Our results show that the microstructure of CaFe 2 As 2 is influenced strongly by the crystal growth conditions and by subsequent heat treatment. The presence of Ca and As vacancies and FeAs nanoprecipitates affect the mechanical behavior significantly. In addition, the onset stress for the collapsed tetragonal transition decreases gradually as the temperature decreases. These experimental results are discussed primarily in terms of the formation of As-As bonds, which is the essential feature of this mechanism for superelasticity. Our research outcomes provide a more fundamental understanding of the superelasticity exhibited by CaFe 2 As 2 under uni-axial compression.

36 MATERIALS SCIENCE↗