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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology

Refrigerator technology has advanced significantly over the last couple of decades. Today’s refrigerators use only about 25% of the energy that was required to power models built in 1975. Even as they continually improve efficiency to meet standards, refrigerators have increased in size by almost 20%, added energy-consuming features such as through-the-door ice, and provide more benefits than ever before. However, a few challenges and technology gaps are preventing further improvement of the demand responsiveness and efficiency of the refrigerators. One of the major technology gaps in existing refrigerators is their outdated de-icing process. When the evaporator generates frost, an old-fashioned resistive heating element melts the ice. Most refrigerators have a timed defrost cycle, rather than an active system that could monitor the state of the frost. In these systems, not only is the precious electricity used at its least efficient form of conversion (direct conversion of electricity to heat), but also all the latent heat associated with the ice is wasted during the melting process. On top of that, the refrigerator needs to work harder to pull the temperature down after defrosting, and, last but not least, the food quality is severely impacted by the temperature swings during the defrost cycle. According to a study, the EU alone wastes 89 million tons of food in the supply chain every year. Any temperature swing during defrosting (about 6F according to Emerson for low-temperature cases) can negatively impact the shelf life of meat and other products for multiple days. All these issues can happen during the peak demand time of the electric grid. Unlike the conventional systems, the proposed novel advanced micro-vibrational deicing process uses no heat for defrosting. Instead, it uses the micro vibrations generated by a piezoelectric or vibration-generating module to mechanically break ice from the heat exchanger almost instantaneously. The project titled “Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology, performed by Ultrasonic Technology Solutions, LLC (UTS) of Knoxville, TN, in collaboration with Emerson (now Copeland), represents the final phase of a multi-year effort funded under the U.S. Department of Energy’s Building Technologies Office (BTO) BENEFIT FOA 2020. Initiated on October 1, 2021, and completed after a nine-month no-cost extension ending September 30, 2025, this project aimed to develop and validate a novel micro-vibrational mechanical defrosting system, achieving more than 25% improvement in defrosting energy efficiency over conventional baseline defrosting technologies. Over sixteen quarters, the project advanced from fundamental ice-mechanical characterization and prototype development to full-scale system integration and validation. Initial efforts established project management infrastructure and characterized ice adhesion properties, followed by the design and fabrication of early aluminum-based prototypes for resonance frequency testing. Subsequent quarters saw rapid technical progression, including the identification of optimal piezoelectric and motor-based vibration mechanisms, the demonstration of effective de-icing over 6x6-inch aluminum surfaces. The team achieved its Go/No-Go milestone by exceeding the 25% energy-efficiency improvement target—reaching up to 3,340% under optimized conditions—and later confirmed that motor-driven systems offered superior performance and energy efficiency compared to piezoelectric alternatives. Continued refinement led to the development of amplifier systems on printed circuit boards, improved control and instrumentation hardware, and integration into full-scale heat exchanger (HX) prototypes at both UTS and Copeland facilities. Multiple vibration-mounting studies and frost-growth experiments guided mechanical optimization and noise-mitigation strategies, achieving a 17.5 dB reduction in sound pressure level and verifying robust mechanical performance. Advanced analyses, including modal and harmonic simulations, established a quantitative understanding of vibrational behavior and de-icing efficiency across >1000 cm² systems. The final project phase successfully demonstrated scalable integration within reach-in and chest freezer prototypes, confirmed >25% efficiency improvements in large-area systems, and completed a comprehensive business model and scale-up strategy identifying electric defrost systems as the primary beachhead market. The culmination of this DOE-supported effort establishes micro-vibrational defrosting as a viable, high-efficiency, low-noise, and demand-flexible de-icing technology, paving the way for commercial deployment and broader application in next-generation refrigeration systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2014

Aeroacoustic Evaluation of Flap and Landing Gear Noise Reduction Concepts

Aeroacoustic measurements for a semi-span, 18% scale, high-fidelity Gulfstream aircraft model are presented. The model was used as a test bed to conduct detailed studies of flap and main landing gear noise sources and to determine the effectiveness of numerous noise mitigation concepts. Using a traversing microphone array in the flyover direction, an extensive set of acoustic data was obtained in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel with the facility in the acoustically treated open-wall (jet) mode. Most of the information was acquired with the model in a landing configuration with the flap deflected 39 deg and the main landing gear alternately installed and removed. Data were obtained at Mach numbers of 0.16, 0.20, and 0.24 over directivity angles between 56 deg and 116 deg, with 90 deg representing the overhead direction. Measured acoustic spectra showed that several of the tested flap noise reduction concepts decrease the sound pressure levels by 2 - 4 dB over the entire frequency range at all directivity angles. Slightly lower levels of noise reduction from the main landing gear were obtained through the simultaneous application of various gear devices. Measured aerodynamic forces indicated that the tested gear/flap noise abatement technologies have a negligible impact on the aerodynamic performance of the aircraft model.

Khorrami, Mehdi R.↗
DOE OSTI2025

Demonstrating magnetic field robustness and reducing temporal T1 noise in transmon qubits through magnetic field engineering

The coherence of superconducting transmon qubits is often disrupted by fluctuations in the energy relaxation time (T1), limiting their performance for quantum computing. While background magnetic fields can be harmful to superconducting devices, we demonstrate that both trapped magnetic flux and externally applied static magnetic fields can suppress temporal fluctuations in T1 without significantly degrading its average value or qubit frequency. Using a three-axis Helmholtz coil system, we applied calibrated magnetic fields perpendicular to the qubit plane during cooldown and operation. Remarkably, transmon qubits based on tantalum-capped niobium (Nb/Ta) capacitive pads and aluminum-based Josephson junctions (JJs) maintained T1 lifetimes near 300 μs even when cooled in fields as high as 600 mG. Both trapped flux up to 600 mG and applied fields up to 400 mG reduced T1 fluctuations by more than a factor of two, while higher field strengths caused rapid coherence degradation. We attribute this stabilization to the polarization of paramagnetic impurities, the role of trapped flux as a sink for non-equilibrium quasiparticles (QPs), and partial saturation of fluctuating two-level systems (TLSs). These findings challenge the conventional view that magnetic fields are inherently detrimental and introduce a strategy for mitigating noise in superconducting qubits, offering a practical path toward more stable and scalable quantum systems.

Abdisatarov, Bektur [Fermilab; Jefferson Lab]↗
NASA NTRS2014

Aerodynamic Measurements of a Gulfstream Aircraft Model With and Without Noise Reduction Concepts

Steady and unsteady aerodynamic measurements of a high-fidelity, semi-span 18% scale Gulfstream aircraft model are presented. The aerodynamic data were collected concurrently with acoustic measurements as part of a larger aeroacoustic study targeting airframe noise associated with main landing gear/flap components, gear-flap interaction noise, and the viability of related noise mitigation technologies. The aeroacoustic tests were conducted in the NASA Langley Research Center 14- by 22-Foot Subsonic Wind Tunnel with the facility in the acoustically treated open-wall (jet) mode. Most of the measurements were obtained with the model in landing configuration with the flap deflected at 39º and the main landing gear on and off. Data were acquired at Mach numbers of 0.16, 0.20, and 0.24. Global forces (lift and drag) and extensive steady and unsteady surface pressure measurements were obtained. Comparison of the present results with those acquired during a previous test shows a significant reduction in the lift experienced by the model. The underlying cause was traced to the likely presence of a much thicker boundary layer on the tunnel floor, which was acoustically treated for the present test. The steady and unsteady pressure fields on the flap, particularly in the regions of predominant noise sources such as the inboard and outboard tips, remained unaffected. It is shown that the changes in lift and drag coefficients for model configurations fitted with gear/flap noise abatement technologies fall within the repeatability of the baseline configuration. Therefore, the noise abatement technologies evaluated in this experiment have no detrimental impact on the aerodynamic performance of the aircraft model.

Neuhart, Dan H.↗
DOE OSTI2025

Online thermal profile prediction for large format additive manufacturing: A hybrid CNN-LSTM based approach

Large format additive manufacturing (LFAM) is an advanced 3D printing technique that efficiently fabricates large-scale components through a layer-by-layer extrusion and deposition process. Accurate surface layer temperature monitoring is essential to prevent manufacturing failures and ensure final product quality. Traditional physics-based offline approaches for simulating thermal behavior are often inefficient and complex, posing challenges on real-time, in-situ monitoring. Here, to address this, we propose a data-driven hybrid CNN-LSTM model to predict sequential thermal images of arbitrary length using real-time infrared thermal imaging. In this approach, a Convolutional Neural Networks (CNN) is trained offline to capture spatial features, reduce dimensional complexity, and enhance time efficiency, while a stacked Long Short-Term Memory (LSTM) is applied online to capture temporal information for improved prediction of future thermal behavior in subsequent printing layers. Model performance is evaluated using MSE, SSIM, and PSNR metrics and is benchmarked against stacked LSTM and convolutional LSTM models, demonstrating superior accuracy and applicability. Additionally, to mitigate noise from moving extruders and gantry backgrounds in thermal images, a fine-tuned semantic segmentation model is implemented offline to extract printing geometry, enabling precise temperature tracking along the tool path for further thermal analysis. The frameworks developed in this study significantly advance temperature monitoring, thermal analysis, and in-situ manufacturing control for LFAM, bridging the gap between theoretical modeling and practical application.

Geometry extraction↗
DOE OSTI2025

Engineering spin coherence in core-shell diamond nanocrystals

Fluorescent diamond nanocrystals can host spin qubit sensors capable of probing the physical properties of biological systems with nanoscale spatial resolution. Sub-100 nm diamond nanosensors can readily be delivered into intact cells and even living organisms. However, applications beyond current proof-of-principle experiments require a substantial increase in sensitivity, which is limited by surface induced charge instability and electron-spin dephasing. In this work, we utilize engineered core-shell structures to achieve a drastic increase in qubit coherence times (T 2 ) from 1.1 to 35 μs in bare nanodiamonds to upward of 52 to 87 μs. We use electron-paramagnetic-resonance results to present a band bending model and connect silica encapsulation to the removal of deleterious mid-gap surface states that are negatively affecting the qubit’s spin properties. Combined with a 1.9-fold increase in particle luminescence these advances correspond to up to two-order-of-magnitude reduction in integration time. Probing qubit dynamics at a single particle level further reveals that the noise characteristics fundamentally change from a bath with spins that rearrange their spatial configuration during the course of an experiment to a more dilute static bath. The observed results shed light on the underlying mechanisms governing fluorescence and spin properties in diamond nanocrystals and offer an effective noise mitigation strategy based on engineered core-shell structures.

core-shell↗
DOE OSTI2025

State Dependent Optimization with Quantum Circuit Cutting

Quantum circuits can be reduced through optimization to better fit the constraints of quantum hardware. One such method, initial-state dependent optimization (ISDO), reduces gate count by leveraging knowledge of the input quantum states. Surprisingly, we found that ISDO is broadly applicable to the downstream circuits produced by circuit cutting. Circuit cutting also requires measuring upstream qubits and has some flexibility of selection observables to do reconstruction. Therefore, we propose a state-dependent optimization (SDO) framework that incorporates ISDO, our newly proposed measure-state dependent optimization (MSDO), and a biased observable selection strategy. Building on the strengths of the SDO framework and recognizing the scalability challenges of circuit cutting, we propose nonseparate circuit cutting-a more flexible approach that enables optimizing gates without fully separating them. We validate our methods on noisy simulations of QAOA, QFT, and BV circuits. Results show that our approach consistently mitigates noise and improves overall circuit performance, demonstrating its promise for enhancing quantum algorithm execution on near-term hardware.

Li, Xinpeng↗
DOE OSTI2024

Deep learning-based temporal deconvolution for photon time-of-flight distribution retrieval

The acquisition of the time of flight (ToF) of photons has found numerous applications in the biomedical field. Over the last decades, a few strategies have been proposed to deconvolve the temporal instrument response function (IRF) that distorts the experimental time-resolved data. However, these methods require burdensome computational strategies and regularization terms to mitigate noise contributions. Herein, we propose a deep learning model specifically to perform the deconvolution task in fluorescence lifetime imaging (FLI). The model is trained and validated with representative simulated FLI data with the goal of retrieving the true photon ToF distribution. Its performance and robustness are validated with well-controlled in vitro experiments using three time-resolved imaging modalities with markedly different temporal IRFs. The model aptitude is further established with in vivo preclinical investigation. Overall, these in vitro and in vivo validations demonstrate the flexibility and accuracy of deep learning model-based deconvolution in time-resolved FLI and diffuse optical imaging.

Pandey, Vikas (ORCID:0000000154771095)↗
DOE OSTI2024

Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete

Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Detection of high-frequency gravitational waves using SRF cavities

Today, apart from some isolated R\&D efforts, there are no GW experiments, yet which explore a large part of the vast frequency range above the LIGO/Virgo band. It is planned to establish an experiment at DESY and Fermilab to search for high-frequency GWs in the frequency range of 10\,kHz to 100\,MHz. The basic idea is to use superconducting radiofrequency (SRF) cavities to detect tiny harmonic deformations induced by GWs which change the boundary conditions of the oscillating electromagnetic field. This paper summarizes the challenging environmental boundary requirements, and the R\&D to operate a cavity using a LLRF system which pushes beyond state-of-the-art accuracy and resolutions and a seismic noise mitigated cryostat at 1.8\,K. The focus of this paper is the warm and cold commissioning of a prototype cavity, built 20 years ago during the MAGO collaboration, and its first measurement in our collaborative research project.

Giaccone, Bianca [Fermilab]↗
DOE OSTI2024

Scattering wave packets of hadrons in gauge theories: Preparation on a quantum computer

Quantum simulation holds promise of enabling a complete description of high-energy scattering processes rooted in gauge theories of the Standard Model. A first step in such simulations is preparation of interacting hadronic wave packets. To create the wave packets, one typically resorts to adiabatic evolution to bridge between wave packets in the free theory and those in the interacting theory, rendering the simulation resource intensive. In this work, we construct a wave-packet creation operator directly in the interacting theory to circumvent adiabatic evolution, taking advantage of resource-efficient schemes for ground-state preparation, such as variational quantum eigensolvers. By means of an ansatz for bound mesonic excitations in confining gauge theories, which is subsequently optimized using classical or quantum methods, we show that interacting mesonic wave packets can be created efficiently and accurately using digital quantum algorithms that we develop. Specifically, we obtain high-fidelity mesonic wave packets in the Z 2 and U(1) lattice gauge theories coupled to fermionic matter in 1+1 dimensions. Our method is applicable to both perturbative and non-perturbative regimes of couplings. The wave-packet creation circuit for the case of the Z 2 lattice gauge theory is built and implemented on the Quantinuum H1-1 trapped-ion quantum computer using 13 qubits and up to 308 entangling gates. The fidelities agree well with classical benchmark calculations after employing a simple symmetry-based noise-mitigation technique. This work serves as a step toward quantum computing scattering processes in quantum chromodynamics.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

The regression intersection method of adjusting image data for band ratioing

Estimation of the combined path radiance and sensor offset terms is essential in adjusting multispectral image radiance measurements for band ratioing. Commonly applied techniques for making this estimate have required assumptions or ancillary information regarding the reflectance properties of surface materials. This paper presents a technique that is unique in that it provides absolute (not just relative) statistically-derived estimates without the use of ancillary information. It is termed the regression intersection method (RIM). RIM is based on contrasts between the spectral properties of various homogeneous areas in rugged terrain. These areas are selected by examination of the image data alone. Bispectral regression (first principal component) lines are determined for each area and are projected, in pairs, to intersection points. Ideally, the coordinates of these points must equal the measurements for zero ground radiance since that is the only condition under which spectrally different materials can have the same radiance values. The median result from several site-pair and band-pair comparisons is used in order to statistically mitigate noise and minor variations due to natural variability. Tests show that the method is successful in determining correction values for the image data that result in maximum removal of the topographic effect in ratio images.

Crippen, Robert E.↗
NASA NTRS1991

Demonstration of automated proximity and docking technologies

An autodock was demonstrated using straightforward techniques and real sensor hardware. A simulation testbed was established and validated. The sensor design was refined with improved optical performance and image processing noise mitigation techniques, and the sensor is ready for production from off-the-shelf components. The autonomous spacecraft architecture is defined. The areas of sensors, docking hardware, propulsion, and avionics are included in the design. The Guidance Navigation and Control architecture and requirements are developed. Modular structures suitable for automated control are used. The spacecraft system manager functions including configuration, resource, and redundancy management are defined. The requirements for autonomous spacecraft executive are defined. High level decisionmaking, mission planning, and mission contingency recovery are a part of this. The next step is to do flight demonstrations. After the presentation the following question was asked. How do you define validation? There are two components to validation definition: software simulation with formal and vigorous validation, and hardware and facility performance validated with respect to software already validated against analytical profile.

Anderson, Robert L.↗
NASA NTRS2008

International Space Station USOS Crew Quarters Development

The International Space Station (ISS) United States Operational Segment (USOS) currently provides a Temporary Sleep Station (TeSS) as crew quarters for one crewmember in the Laboratory Module. The Russian Segment provides permanent crew quarters (Kayutas) for two crewmembers in the Service Module. The TeSS provides limited electrical, communication, and ventilation functionality. A new permanent rack sized USOS ISS Crew Quarters (CQ) is being developed. Up to four CQs can be installed into the Node 2 element to increase the ISS crewmember size to six. The new CQs will provide private crewmember space with enhanced acoustic noise mitigation, integrated radiation reduction material, controllable airflow, communication equipment, redundant electrical systems, and redundant caution and warning systems. The rack sized CQ is a system with multiple crewmember restraints, adjustable lighting, controllable ventilation, and interfaces that allow each crewmember to personalize their CQ workspace. Providing an acoustically quiet and visually isolated environment, while ensuring crewmember safety, is critical for obtaining crewmember rest and comfort to enable long term crewmember performance. The numerous human factor, engineering, and program considerations during the concept, design, and prototyping are outlined in the paper.

Broyan, James Lee, Jr.↗
NASA NTRS2008

Frequency-Tuneable Pre-Stabilized Lasers for LISA via Sideband Locking

Laser frequency noise mitigation is one of the most challenging aspects of the LISA interferometric measurement system. The unstabilized frequency fluctuations must be suppressed by roughly twelve orders of magnitude in order to achieve a stability sufficient for gravitational wave detection. This enormous suppression will be achieved through a combination of stabilization and common-mode rejection. The stabilization component will itself be achieved in two stages: pre-stabilization to a local optical cavity followed by arm-locking to some combination of the inter-spacecraft distances. In order for these two stabilization stages to work simultaneously, the lock-point of the pre-stabilization loop must be frequency tunable. The current baseline stabilization technique, locking to an optical cavity, does not provide tunability between cavity resonance, which are typically spaced by 100s of MHz. Here we present a modification to the traditional Pound-Drever-Hall cavity locking technique that allows the laser to be locked to a cavity resonance with an adjustable frequency offset. This technique requires no modifications to the optical cavity itself, thus preserving the stability of the frequency reference. We present measurements of the system stability, demonstrating that the pre-stabilization level satisfies LISA requirements. We also present a demonstration of a phase-lock loop which utilizes the tunable sideband locking technique as a pre-stabilizations tage. The performance of the pre-stabilized phase-lock-loop indicates that the tunable sideband technique will meet the requirements as an actuator for arm-locking in LISA.

Thorpe, James Ira↗
NASA NTRS2008

Development of arrays of position-sensitive microcalorimeters for Constellation-X

We are developing arrays of position-sensitive transition-edge sensor (POST) X-ray detectors for future astronomy missions such as NASA's Constellation-X. The POST consists of multiple absorbers thermally coupled to one or more transition-edge sensor (TES). Each absorber element has a different thermal coupling to the TES. This results in a distribution of different pulse shapes and enables position discrimination between the absorber elements. POST'S are motivated by the desire to achieve the largest possible focal plane area with the fewest number of readout channels and are ideally suited to increasing the Constellation-X focal plane area, without comprising on spatial sampling. Optimizing the performance of POST'S requires careful design of key parameters such as the thermal conductances between the absorbers, TES and the heat sink. as well as the absorber heat capacities. Using recently developed signal processing algorithms we have investigated the trade-off between position-sensitivity, energy resolution and pulse decay time. based on different device design parameters for PoST's. Our new generation of PoST's utilize technology successfully developed on high resolution (approximately 2.5eV) single pixels arrays of Mo/Au TESs. also under development for Constellation-X. This includes noise mitigation features on the TES and low resistivity electroplated absorbers. We report on the first experimental results from these new one and two-channel PoST"s, consisting of all Au and composite Au/Bi absorbers, which are designed to achieve an energy resolution of < 10 eV. coupled with count-rates of 100's per pixel per second and position sensitivity over the energy range 0.3-10 keV.

Smith, S. J.↗
NASA NTRS2008

Frequency-tunable Pre-stabilized Lasers for LISA via Sideband-locking

Laser frequency noise mitigation is one of the most challenging aspects of the LISA interferometric measurement system. The unstabilized frequency fluctuations must be suppressed by roughly twelve orders of magnitude in order to achieve stability sufficient for gravitational wave detection. This enormous suppression will be achieved through a combination of stabilization and common-mode rejection. The stabilization component will itself be achieved in two stages: pre-stabilization to a local optical cavity followed by arm-locking to some combination of the inter-spacecraft distances. In order for these two stabilization stages to work simultaneously, the lock-point of the pre-stabilization loop must be frequency tunable. The current baseline stabilization technique, locking to an optical cavity, does not provide tunability between cavity resonances, which are typically spaced by 100s of MHz. Here we present a modification to the traditional Pound-Drever-Hall cavity locking technique that allows the laser to be locked to a cavity resonance with an adjustable frequency offset. This technique requires no modifications to the optical cavity itself, thus preserving the stability of the frequency reference. We present measurements of the system performance and demonstrate that we can meet implement the first two stages of stabilization.

Livas, Jeffrey C.↗
NASA NTRS2008

International Space Station USOS Crew Quarters On-orbit vs Design Performance Comparison

The International Space Station (ISS) United States Operational Segment (USOS) received the first two permanent ISS Crew Quarters (CQ) on Utility Logistics Flight Two (ULF2) in November 2008. Up to four CQs can be installed into the Node 2 element to increase the ISS crewmember size to six. The CQs provide private crewmember space with enhanced acoustic noise mitigation, integrated radiation reduction material, communication equipment, redundant electrical systems, and redundant caution and warning systems. The racksized CQ is a system with multiple crewmember restraints, adjustable lighting, controllable ventilation, and interfaces that allow each crewmember to personalize their CQ workspace. The deployment and initial operational checkout during integration of the ISS CQ to the Node is described. Additionally, the comparison of on-orbit to original design performance is outlined for the following key operational parameters: interior acoustic performance, air flow rate, temperature rise, and crewmember feedback on provisioning and restraint layout.

Broyan, James Lee, Jr.↗