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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Embedded Sensors for Measuring Surface Regression

The development and evaluation of new hybrid and solid rocket motors requires accurate characterization of the propellant surface regression as a function of key operational parameters. These characteristics establish the propellant flow rate and are prime design drivers affecting the propulsion system geometry, size, and overall performance. There is a similar need for the development of advanced ablative materials, and the use of conventional ablatives exposed to new operational environments. The Miniature Surface Regression Sensor (MSRS) was developed to serve these applications. It is designed to be cast or embedded in the material of interest and regresses along with it. During this process, the resistance of the sensor is related to its instantaneous length, allowing the real-time thickness of the host material to be established. The time derivative of this data reveals the instantaneous surface regression rate. The MSRS could also be adapted to perform similar measurements for a variety of other host materials when it is desired to monitor thicknesses and/or regression rate for purposes of safety, operational control, or research. For example, the sensor could be used to monitor the thicknesses of brake linings or racecar tires and indicate when they need to be replaced. At the time of this reporting, over 200 of these sensors have been installed into a variety of host materials. An MSRS can be made in either of two configurations, denoted ladder and continuous (see Figure 1). A ladder MSRS includes two highly electrically conductive legs, across which narrow strips of electrically resistive material are placed at small increments of length. These strips resemble the rungs of a ladder and are electrically equivalent to many tiny resistors connected in parallel. A substrate material provides structural support for the legs and rungs. The instantaneous sensor resistance is read by an external signal conditioner via wires attached to the conductive legs on the non-eroding end of the sensor. The sensor signal can be transmitted from inside a high-pressure chamber to the ambient environment, using commercially available feedthrough connectors. Miniaturized internal recorders or wireless data transmission could also potentially be employed to eliminate the need for producing penetrations in the chamber case. The rungs are designed so that as each successive rung is eroded away, the resistance changes by an amount that yields a readily measurable signal larger than the background noise. (In addition, signal-conditioning techniques are used in processing the resistance readings to mitigate the effect of noise.) Hence, each discrete change of resistance serves to indicate the arrival of the regressing host material front at the known depth of the affected resistor rung. The average rate of regression between two adjacent resistors can be calculated simply as the distance between the resistors divided by the time interval between their resistance jumps. Advanced data reduction techniques have also been developed to establish the instantaneous surface position and regression rate when the regressing front is between rungs.

Gramer, Daniel J.↗
DOE OSTI2021

Evolution of Microstructure and Surface Characteristics of FeCrAl alloys when Subjected to Flow Boiling Testing

FeCrAl alloys are candidate materials for manufacturing accident-tolerant fuel (ATF) cladding intended for light water reactors to increase fuel reliability and safety during design-basis and beyond-design-basis accident scenarios. The evolution of the materials' surface characteristics, microstructure, and mechanical properties when exposed to the Critical Heat Flux (CHF) in flow boiling testing is crucial for safety analysis while providing insights into their thermal-hydraulic performance in nuclear reactors. After CHF, the surface chemistry of two FeCrAl alloys, APMT and C26M, was studied to understand their evolution at the early stage of high-temperature excursions in short time periods. The results indicated a thin layer composed of oxides and hydroxides of Al, Cr, and Fe with varying proportions at different depths in the layer, as indicated by X-ray photoelectron spectroscopy (XPS) and depth profiling. The cross-sections prepared by focused ion beam (FIB) revealed the growth of an oxide layer, in the range of 90-180 nm thick, on the alloys' surfaces. The evolution of the materials' surface chemistry also led to a noticeable post CHF excursion increase in their wettability, with a slight increase in roughness. Further, the investigation of the materials' mechanical properties indicated a modest increase in hardness by 10-15% as well as an increase in their yield strength, as evidenced by the microindentation and ring compression tests conducted before and after CHF testing. Scanning electron Microscopy (SEM) and X-ray diffraction (XRD) were used to investigate microstructural features of the materials and their changes after CHF treatment.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
DOE OSTI2020

Brilliant Execution of Smart Labs: Employing Best Practices to Improve Safety and Reduce Energy for Sustainable Labs: Preprint

Laboratory buildings often dominate the energy use on research campuses, consuming three to four times the energy of a typical office building. In most cases, these facilities are defined as “mission critical,” with excessive energy use as simply an unfortunate truth that cannot be avoided without compromising safety. However, case studies indicate cost savings opportunities of up to 40% in laboratories (compared to standard practices) by employing energy efficient design strategies that also improve the safety of lab spaces (Better Buildings 2018). To help stakeholders implement improvement measures, the Smart Labs Toolkit describes a proven approach to optimizing performance of laboratories and critical control environments in new or existing facilities. The Toolkit outlines distinct phases for building a successful Smart Labs program that include: Plan, Assess, Optimize, and Manage. Each phase has specific tasks, training videos, and resources to educate users, support the efforts of key stakeholders, and maximize benefits for the organization in implementing high-performance labs. The Toolkit also includes case studies from the 17 Better Buildings Smart Labs Accelerator partners, sharing lessons learned and supporting the Smart Labs approach to safe, efficient world class science. This paper reviews the technology choices for implementing Smart Labs ventilation strategies, controls, and other efficiency measures. Better Building Smart Lab Accelerator partners provide case study examples of safety and energy-savings results of using Smart Labs approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Safety Performance of Airborne Separation: Preliminary Baseline Testing

The Safety Performance of Airborne Separation (SPAS) study is a suite of Monte Carlo simulation experiments designed to analyze and quantify safety behavior of airborne separation. This paper presents results of preliminary baseline testing. The preliminary baseline scenario is designed to be very challenging, consisting of randomized routes in generic high-density airspace in which all aircraft are constrained to the same flight level. Sustained traffic density is varied from approximately 3 to 15 aircraft per 10,000 square miles, approximating up to about 5 times today s traffic density in a typical sector. Research at high traffic densities and at multiple flight levels are planned within the next two years. Basic safety metrics for aircraft separation are collected and analyzed. During the progression of experiments, various errors, uncertainties, delays, and other variables potentially impacting system safety will be incrementally introduced to analyze the effect on safety of the individual factors as well as their interaction and collective effect. In this paper we report the results of the first experiment that addresses the preliminary baseline condition tested over a range of traffic densities. Early results at five times the typical traffic density in today s NAS indicate that, under the assumptions of this study, airborne separation can be safely performed. In addition, we report on initial observations from an exploration of four additional factors tested at a single traffic density: broadcast surveillance signal interference, extent of intent sharing, pilot delay, and wind prediction error.

Consiglio, Maria C.↗
NASA NTRS1983

Longitudinal flying qualities criteria for single-pilot instrument flight operations

Modern estimation and control theory, flight testing, and statistical analysis were used to deduce flying qualities criteria for General Aviation Single Pilot Instrument Flight Rule (SPIFR) operations. The principal concern is that unsatisfactory aircraft dynamic response combined with high navigation/communication workload can produce problems of safety and efficiency. To alleviate these problems. The relative importance of these factors must be determined. This objective was achieved by flying SPIFR tasks with different aircraft dynamic configurations and assessing the effects of such variations under these conditions. The experimental results yielded quantitative indicators of pilot's performance and workload, and for each of them, multivariate regression was applied to evaluate several candidate flying qualities criteria.

Stengel, R. F.↗
NASA NTRS1986

Longitudinal flying qualitites criteria for single-pilot instrument flight operations

Modern estimation and control theory, flight testing, and statistical analysis were used to deduce flying qualities criteria for General Aviation Single Pilot Instrument Flight Rule (SPIFR) operations. The principal concern is that unsatisfactory aircraft dynamic response combined with high navigation/communication workload can produce problems of safety and efficiency. To alleviate these problems, the relative importance of these factors must be determined. This objective was achieved by flying SPIFR tasks with different aircraft dynamic configurations and assessing the effects of such variations under these conditions. The experimental results yielded quantitative indicators of pilot's performance and workload, and for each of them, multivariate regression was applied to evaluate several candidate flying qualities criteria.

Bar-Gill, A.↗
DOE OSTI2025

Housing-Performance Atlas of Baltimore Row Homes: Archetype-Based Multi-Hazard Baseline of Energy, Heat, Survivability, and Durability

Baltimore’s historic row-home neighborhoods face escalating risks to energy, heat, and durability under intensifying climate stress. This study develops a Housing-Performance Atlas that quantifies multi-hazard performance for eight representative archetypes using DesignBuilder/EnergyPlus Version 7.3.1.003, under Baltimore TMY3 boundary conditions. Performance is evaluated across the following four adaptation domains: energy use intensity, passive survivability during 72 h outage events, roof overheating exposure (>150 °F exceedance hours), and material service life derived from ISO 15686 and synthesized into Lean and Full Deficit Indices for comparative resilience ranking. Results show that EUI ranged from 46.7 to 67.6 kBtu ft −2 ·yr −1 , survivability from 0 to 23 h, and roof temperatures exceeded 150 °F for 150–210 h, shortening roof service life by up to 10 years. Composite Lean and Full Deficit Indices ranged 7.8–92.4, ranking Model 5 (end-unit, flat roof, two-story with basement) as the most resilient configuration and Model 8 (end-unit, pitched roof, three-story above-grade) as the least resilient due to compounded overheating and energy losses. Heat-related domains accounted for nearly 70% of overall resilience deficits, confirming thermal safety and roof reflectivity as retrofit priorities. The Housing-Performance Atlas establishes a reproducible diagnostic framework linking simulation, service life, and resilience metrics to guide cost-effective, climate-responsive retrofits in Baltimore’s aging urban housing stock.

Housing-Performance atlas↗
DOE OSTI2025

Multi-criteria thermal resilience certification scheme for indoor built environments during heat waves

With climate change, the indoor built environment is expected to significantly influence the occupant's safety and well-being. A novel multi-criteria thermal resilience certification scheme for indoor built environments during extreme heat events is proposed in this paper. The certification scheme considers overheating, thermal comfort, heat stress, and hygrothermal discomfort in built environments. These criteria are quantified using key performance indicators like indoor overheating degree, hours of exceedance, wet-bulb globe temperature, and heat index, respectively. This scheme is developed based on existing best practices like standards, rating systems, and literature. The scheme is implemented on a benchmark building energy performance model for detached post-World War II dwellings in Belgium as a case study using weather data measured from the City of Brussels. The indoor overheating in the reference dwelling is assessed with a static threshold of 27 °C for the bedrooms and adaptive thresholds for other areas. The analysis found that the building performance is within the defined threshold levels throughout the heat wave duration for all criteria. Therefore, the reference dwelling got a maximum attainable score of four points and is rated five-star for thermal resilience during heat waves. The proposed certification scheme is intended as a standardized framework and highlights the need for further revisions in building performance policies and guidelines.

Climate change↗
NASA NTRS1977

An objective determination of +Gz acceleration tolerance

Until recently, human +Gz acceleration tolerance has relied solely on subjective criteria relating to loss of vision. By use of newly developed noninvasive instrumentation using a transcutaneous Doppler flow system, objective end point criteria have been developed based on measured blood flow to the head. The system consists of miniature 8 MHz Doppler sensors (2 x 1 x 0.5 cm) placed on the forehead over both frontal branches of the temporal arteries to detect blood flow velocity from back scattered ultrasound. Its use has allowed for correlation of altered, decreased and actual reversal of eye level blood flow with subsequent central light loss. Over 100 subjects have now been studied during more than 2,000 centrifuge runs. Objective changes in temporal artery flow velocity consistently preceded visual degradation for each subject during all acceleration profiles. No subject has gone unconscious without first exhibiting a minimum 6 sec of total flow cessation. Retrograde flow followed by complete flow cessation always preceded central light loss. Results indicate that this method can be successfully used with a wide variety of tasks during exposure to +Gz acceleration. It is recommended for use during evaluation of protective maneuvers or devices on the centrifuge or during actual flight in high performance aircraft. It may also serve as a potential safety monitor during space Shuttle re-entry if there is doubt about a passenger's cardiovascular status.

Unconsciousness/prevention & control↗
DOE OSTI2021

Proton Nuclear Magnetic Resonance (H NMR) of Glycolate in Real Waste: Developing and Testing Analytical Methods for the Savannah River Site Liquid Waste System

In preparation for implementing the NG acid flowsheet for the SRS LWS, analytical methods for determining glycolate at low concentration are desired to support system management and safety. Previous work documented that the IC method performed well for samples with low to moderate ionic strength. That work also included a scoping effort to determine if an alternate analytical strategy using H NMR would complement and extend the capabilities of the IC method. The H NMR scoping results indicated that the method had the potential to expand glycolate analysis in LWS samples to higher ionic strength tanks/solutions. The scope of this work is to develop innovative proton NMR techniques, including demonstrating ion exchange decontamination protocols needed for application of the technique to real waste samples. Part of radioactive waste processing at SRS uses formic acid to reduce oxidized (Hg 2+ ) to more volatile elemental Hg for steam striping, collecting, and disposal. Under acidic conditions found in the Chemical Processing Cell (CPC) at the Defense Waste Processing Facility (DWPF), formic acid has a much higher hydrogen generation rate than an alternative reductant, glycolic acid. Thus, an NG acid flowsheet has been developed utilizing glycolic acid with the benefit of easing the need for headspace monitoring requirements for hydrogen and ammonia at DWPF. Low concentrations of glycolate are conservatively assumed to be in the recycle stream, which will collect in the Recycle Collection Tank (RCT). The DWPF recycle stream collected in the RCT has a distinct pathway to the LWS waste tanks that feed the 2H and 3H Evaporator. This route involves transfer of the DWPF recycle to Tank 22 in the Concentration, Storage, and Transfer Facilities (CSTF) followed by transfer to the LWS tank farm/evaporators.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗
NASA NTRS2014

Improving Sensorimotor Adaptation Following Long Duration Space Flight by Enhancing Vestibular Information Transfer

Crewmember adapted to the microgravity state may need to egress the vehicle within a few minutes for safety and operational reasons after gravitational transitions. The transition from one sensorimotor state to another consists of two main mechanisms: strategic and plastic-adaptive and have been demonstrated in astronauts returning after long duration space flight. Strategic modifications represent "early adaptation" - immediate and transitory changes in control that are employed to deal with short-term changes in the environment. If these modifications are prolonged then plastic-adaptive changes are evoked that modify central nervous system function, automating new behavioral responses. More importantly, this longer term adaptive recovery mechanism was significantly associated with their strategic ability to recover on the first day after return to Earth G. We are developing a method based on stochastic resonance to enhance information transfer by improving the brain's ability to detect vestibular signals (Vestibular Stochastic Resonance, VSR) especially when combined with balance training exercises such as sensorimotor adaptability (SA) training for rapid improvement in functional skill, for standing and mobility. This countermeasure to improve detection of vestibular signals is a stimulus delivery system that is wearable/portable providing low imperceptible levels of white noise based binaural bipolar electrical stimulation of the vestibular system (stochastic vestibular stimulation). To determine efficacy of vestibular stimulation on physiological and perceptual responses during otolith-canal conflicts and dynamic perturbations we have conducted a series of studies: We have shown that imperceptible binaural bipolar electrical stimulation of the vestibular system across the mastoids enhances balance performance in the mediolateral (ML) plane while standing on an unstable surface. We have followed up on the previous study showing VSR stimulation improved balance performance in both ML and anteroposterior planes while stimulating in the ML axis only. We have shown the efficacy of VSR stimulations on enhancing physiological and perceptual responses of whole-body orientation during low frequency perturbations (0.1 Hz) on the ocular motor system using a variable radius centrifuge on both physiological (using eye movements) and perceptual responses (using a joystick) to track imposed oscillations. The variable radius centrifuge provides a selective tilting sensation that is detectable only by the otolith organs providing conflicting information from the canal organs of the vestibular system (intra-vestibular conflict). These results indicate that VSR can improve performance in sensory conflict scenarios like that experienced during space flight. We have showed the efficacy of VSR stimulation to improve balance and locomotor control on subjects exposed to continuous, sinusoidal lateral motion of the support surface while walking on a treadmill while viewing perceptually matched linear optic flow. We have shown the safety of short term continuous use of up to 4 hours of VSR stimulation and its efficacy in improving balance and locomotor function in Parkinson's Disease patients. This technique for improving vestibular signal detection may thus provide additional information to improve strategic abilities. We hypothesize that VSR stimulation will act synergistically with SA training to improve adaptability by increased utilization of vestibular information and therefore serve to optimize and personalize the SA countermeasure prescription. This forms the basis of its usefulness both as a training modality and further help in significantly reducing the number of days required to recover functional performance to preflight levels after long duration space flight.

Mulavara, A. P.↗
DOE OSTI2024

Impacts of Irradiation Structural Behavior on Thermal Hydraulics Safety Analysis to Support MURR LEU Conversion

The University of Missouri Research Reactor (MURR) located in Columbia, Missouri is one of six U.S. High Performance Research Reactors (USHPRR), including one critical facility, that is actively collaborating with U. S. Department of Energy (DOE) National Nuclear Security Administration (NNSA) Material Management and Minimization (M3) Office of Reactor Conversion and Uranium Supply to convert from the use of highly enriched uranium (HEU; ≥20 wt% U-235) to low-enriched uranium (LEU; <20 wt% U-235) fuel. A new type of very high-density LEU fuel based on an alloy of uranium and 10 wt% molybdenum (U-10Mo) is expected to allow the conversion to LEU of MURR, as well as four other USHPRR. MURR has been working with the Reactor Conversion Pillar at Argonne to perform fuel element design and fuel cycle performance analyses, steady-state thermal hydraulics safety analysis, and accident safety analyses in preparation for the conversion of MURR and to support a preliminary safety analysis report for conversion to LEU fuels. Subsequent analyses have also been performed, including transition cycles where all-fresh LEU fuel elements are introduced upon conversion and progressing through reactor operations the core is brought to equilibrium. Thermal hydraulics safety analyses performed as part of the above have employed an assumption on channel gap reduction due to burnup-related phenomena including fuel swelling, irradiation creep, and oxide layer buildup. Recently, a series of structural analyses have been performed on the MURR LEU fuel plates and an element due to significant differences between the plate and element designs of the MURR HEU and LEU fuels. In addition, NUREG-1537 indicates that structural phenomena are to be evaluated. Two separate types of structural analyses were performed for the MURR LEU fuel element: fluid-structure interaction (FSI) and irradiation thermo-mechanical. The FSI analysis evaluated the effects of hydraulic forces on the MURR LEU fuel element to quantify the flow-induced plate deflection, and a minimal impact to the channel gap thickness was predicted under prototypic and bounding conditions. The irradiation thermo-mechanical analysis evaluated the effects of fuel swelling, irradiation creep, and thermal expansion for the MURR LEU plates and the element for prototypic thermal and irradiation conditions based on a high-fidelity approach multiphysics approach. Overall, this thermo-mechanical analysis predicts smaller gap thickness changes in previously limiting regions. Larger changes are predicted in the middle of channels, and for end channels where power density is not typically a maximum. An additional thermo-mechanical analysis was performed for the outermost HEU fuel plate, which showed a similar magnitude of deflection as the outermost LEU plate. Due to substantial differences between the channel gap reductions assumed for the previous safety analyses and those predicted by the irradiation thermo-mechanical analysis, a need to evaluate their impact on the thermal hydraulics safety analyses arose. This report presents the results from the steady-state safety analyses for normal operation as well as the accident analyses for the two most limiting accident scenarios.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2011

International Space Station Acoustics - A Status Report

It is important to control acoustic noise aboard the International Space Station (ISS) to provide a satisfactory environment for voice communications, crew productivity, and restful sleep, and to minimize the risk for temporary and permanent hearing loss. Acoustic monitoring is an important part of the noise control process on ISS, providing critical data for trend analysis, noise exposure analysis, validation of acoustic analysis and predictions, and to provide strong evidence for ensuring crew health and safety, thus allowing Flight Certification. To this purpose, sound level meter (SLM) measurements and acoustic noise dosimetry are routinely performed. And since the primary noise sources on ISS include the environmental control and life support system (fans and airflow) and active thermal control system (pumps and water flow), acoustic monitoring will indicate changes in hardware noise emissions that may indicate system degradation or performance issues. This paper provides the current acoustic levels in the ISS modules and sleep stations, and is an update to the status presented in 20031. Many new modules, and sleep stations have been added to the ISS since that time. In addition, noise mitigation efforts have reduced noise levels in some areas. As a result, the acoustic levels on the ISS have improved.

Allen, Christopher S.↗
NASA NTRSDate not supplied

International Space Station Acoustics – A Status Report

It is important to control acoustic noise aboard the International Space Station (ISS) to provide a satisfactory environment for voice communications, alarm audibility, and restful sleep, and to minimize the risk for hearing loss. Acoustic monitoring is an important part of the noise control process on ISS, providing critical data for trend analysis, noise exposure analysis, validation of acoustic analyses and predictions, and to provide strong evidence for ensuring crew health and safety, thus allowing Flight Certification. And since the primary noise sources on ISS include the environmental control and life support system’s air revitalization system (fans and airflow) and active thermal control system (pumps and water flow), acoustic monitoring will indicate changes in hardware noise emissions that may indicate system degradation or performance issues. This paper provides the current acoustic levels in the ISS modules and sleep stations, and is an update to the status presented in 2018. Since this last status report, noise levels have remained consistent, but issues with stalled fan noise and unexplained low frequency spectral peaks have caused some exceedances to requirements. Noise levels in the Russian Segment have either remained consistent or have been reduced slightly, except for the new Multipurpose Laboratory Module, which has some significant noise exceedances.

Christopher S Allen↗
NASA NTRS1995

NASA wiring for space applications program

An overview of the NASA Wiring for Space Applications Program and its relationship to NASA's space technology enterprise is given in viewgraph format. The mission of the space technology enterprise is to pioneer, with industry, the development and use of space technology to secure national economic competitiveness, promote industrial growth, and to support space missions. The objectives of the NASA Wiring for Space Applications Program is to improve the safety, performance, and reliability of wiring systems for space applications and to develop improved wiring technologies for NASA flight programs and commercial applications. Wiring system failures in space and commercial applications have shown the need for arc track resistant wiring constructions. A matrix of tests performed versus wiring constructions is presented. Preliminary data indicate the performance of the Tensolite and Filotex hybrid constructions are the best of the various candidates.

Schulze, Norman↗