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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 19 records

Development and flight-testing of modular autonomous cultivation systems for biological plastics upcycling aboard the ISS

Cultivation of microorganisms in space has enormous potential to enable in-situ resource utilization (ISRU) Here, we develop an autonomous payload with fully programmable serial passaging and sample preservation, termed the Modular Open Biological Platform (MOBP), and flight-test the MOBP aboard the International Space Station (ISS) by conducting enzymatic and microbial plastics upcycling experiments. The MOBP is a compact, modular bioreactor system that allows for sustained microbial growth via automated media transfers, such as those for sample collection and storage for terrestrial analyses, and precise data monitoring from integrated sensors. The MOBP was flight-tested with two experiments designed to evaluate biological upcycling of the plastic poly(ethylene terephthalate) (PET). The bioproduct βKA can be polymerized into a nylon-6,6 analog with improved properties for use in the production of a variety of materials. We posit the MOBP will aid in democratizing the execution of synthetic biology in spaceflight towards enabling ISRU.

09 BIOMASS FUELS↗

In-flight performance of the XRISM/Resolve detector system

The Resolve instrument was launched on board the XRISM observatory in early September 2023. The Resolve spectrometer is based on a high-sensitivity X-ray calorimeter detector system (DS) that has been successfully deployed in many ground and sub-orbital spectrometers. However, the Resolve instrument is the first long-term implementation in space. The instrument will provide essential diagnostics for nearly every class of X-ray emitting objects, from galactic supernova remnants to the outskirts of galaxy clusters, without degradation for spatially extended objects. The Resolve DS consists of a 36-pixel microcalorimeter array operated at a heat sink temperature of 50 mK. In pre-flight testing, the DS demonstrated a resolving power of better than 1300 at 6 keV with a simultaneous bandpass from below 0.3 keV to above 12 keV and a timing precision better than 100μs. An anti-coincidence detector placed directly behind the microcalorimeter array effectively suppresses background. The detector energy-resolution budget included terms for interference from the Resolve cooling system and the spacecraft. Additional terms for energy-scale stability, on-orbit effects, and use of mid-grade events were also included, predicting an end-of-life, on-orbit performance for high- and mid-resolution grade events that meet the requirement of 7 eV FWHM at 6 keV. Here, we discuss the actual on-orbit performance of the Resolve DS and compare this with the performance in pre-flight testing, on-orbit predictions, and the almost identical Hitomi/SXS instrument. We will also discuss the on-orbit gain stability, an assessment of on-orbit interference, and measurements of the on-orbit background.

Astronomy and AstroPhysics↗

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Aerial drone fleet deployment optimization with endogenous battery replacements for direct delivery of time-sensitive products

Aerial drones offer a distinct potential to reduce the delivery time and energy consumption for the delivery of time-sensitive and small products. However, there is still a need in the relevant industry to understand the performance of drone-based delivery under different business needs and drone operating conditions. We studied a drone deployment optimization problem for direct delivery of time-sensitive products with release dates to customers maintaining a specified time window. This paper presents a new mixed-integer programming model, new valid inequalities, a new greedy heuristic algorithm, and a Genetic algorithm to help business owners optimally schedule and route their drone fleet minimizing the required fleet size, the required number of additional batteries, and total energy consumption. A realistic feature of the optimization method is that instead of replacing the drone battery after each return to the depot, it keeps track of the remaining energy in the drone battery and decides on battery replacements accounting for the drone routing and the user-specified minimum required battery energy. Numerical results based on real data from drone flight tests and prepared food delivery industry provide insights into the effect of different practical drone operating parameters on the required fleet size, the required number of battery replacements, and energy consumption. Here, results demonstrate that the proposed heuristic algorithm substantially outperforms the accelerated CPLEX in runtime while sacrificing the solution quality by a small amount. Additionally, results show that using a mixed fleet of hexacopter and quadcopter drones reduces the total energy consumption by 48.52% compared to using a homogeneous fleet of only hexacopters.

Drone energy consumption↗

A banner year for solar balloon technology

Solar-powered stratospheric balloons achieved major advancements in test flights, developmental milestones, and operational achievements this year. A solar-powered stratospheric balloon system known as the heliotrope, has emerged as a low-cost platform capable of carrying several pounds of scientific payload to altitudes ranging from 50,000 to 75,000 feet (Bowman et al., 2020; Image 1) for multi-hour level flights. This innovative system has facilitated groundbreaking scientific discoveries in areas such as infrasound and atmospheric composition. Unlike sealed weather balloons that burst, these balloons remain buoyant by retaining hot air within their open envelopes. Because they are solar-powered, they remain aloft as long as the sun remains unobscured.

14 SOLAR ENERGY↗

Drone Flight Data Logs

This dataset represents the open-air tests for the drones when testing different flight scenarios. For some flights we created and tested with a set of onboard sensors. For others we used the native logs for the drones. We recorded relevant conditions for each of the flights to examine environmental issues and weight impacts. We also looked at segmentations of flights to investigate the energy used in each type of flight.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Laser Measurements and Modeling of Shock Tunnel Freestream Velocity and Multispecies Thermal Nonequilibrium

Coherent anti-Stokes Raman scattering (CARS) and nitric oxide molecular tagging velocimetry (NO-MTV) were used to characterize the freestream in Sandia’s Hypersonic Shock Tunnel (HST) using a burst-mode laser operated at 100 kHz. Experiments were performed at nominal freestream velocities of 3 and 4 km/s using both air and N 2 test gas. The CARS diagnostic provides nonequilibrium characterization of the flow by measuring vibrational and rotational temperatures of N 2 and O 2 , which are compared to NO temperatures from separate laser absorption experiments. Simultaneous, collinear freestream velocities were measured using NO MTV along with pitot pressure measurements. Furthermore, this extensive freestream dataset is compared to nonequilibrium CFD that is capable of modeling species-specific, vibrational temperatures throughout the nozzle expansion. Significant nonequilibrium between vibrational and rotational temperatures was measured at each flow condition. N 2 exhibits the most nonequilibrium, followed by O 2 and NO. The CFD model captures this trend, although it consistently overpredicts N 2 and O 2 vibrational temperatures. At 3 km/s, the modeled NO nonequilibrium is underpredicted, whereas it is overpredicted at 4 km/s. Good agreement is seen between CFD and the velocity and rotational temperature measurements. Experiments with water added to the test gas yielded no discernable difference in vibrational relaxation.

Aerodynamics↗

Does class matter? Understanding differential pandemic recovery via a building typology

This study investigates the recovery of building-level footfall from the COVID-19 pandemic using privacy-preserving mobile devices-based footfall data within 60 downtown areas in the USA and Canada. Using clustering, we identify five distinct building typologies based on their characteristics, including rent, quality and recovery rates. The results reveal significant variation of recovery rates by building features. We find negative relationships with footfall recovery for both the percentage of office and remote work tenants and building quality. In contrast, buildings with traditional work tenants and retail functions achieve higher recovery rates. We also test the ‘flight to quality’ hypothesis via on our typology results. High-quality office buildings (Class A+) continue to have high rents but experience low physical footfall recovery, which suggests that this class is not as resilient as portrayed. The findings thus suggest the importance of considering both economic and footfall resilience in evaluating the performance of office buildings.

Covid-19↗

High-count rate effects in event processing for XRISM/ Resolve X-ray microcalorimeter: I. Ground test

The spectroscopic performance of an X-ray microcalorimeter is compromised at high count rates. We utilize the Resolve X-ray microcalorimeter onboard the XRISM satellite to examine the effects observed during high-count rate measurements and propose modeling approaches to mitigate them. We specifically address the following instrumental effects that impact performance: CPU limit, pile-up, and untriggered electrical cross-talk. Experimental data at high count rates were acquired during ground testing using the flight model instrument and a calibration X-ray source. In the experiment, data processing not limited by the performance of the onboard CPU was run in parallel, which cannot be done in orbit. This makes it possible to access the data degradation caused by limited CPU performance. We use these data to develop models that allow for a more accurate estimation of the aforementioned effects. To illustrate the application of these models in observation planning, we present a simulated observation of GX 13+1. Understanding and addressing these issues is crucial to enhancing the reliability and precision of X-ray spectroscopy in situations characterized by elevated count rates.

47 OTHER INSTRUMENTATION↗

Strategies for the in-orbit gain tracking using the modulated X-ray sources for the Resolve microcalorimeter spectrometer on the X-ray Imaging and Spectroscopy Mission

Accurate and precise correction of the gain drift is the key to achieve the required energy resolution of the Resolve microcalorimeter spectrometer on the X-ray Imaging and Spectroscopy Mission (XRISM). Therefore, Resolve is equipped with highly configurable X-ray sources called the modulated X-ray source (MXS). The pulsed nature allows us to separate calibration and astrophysical X-rays by time interval selections. However, undesirable characteristics of the MXS, such as the afterglow X-rays, restrict the allowed configuration range. Moreover, the nonlinear and discontinuous behaviors of the calibration line count rate make the determination of the optimal setting highly complex. The MXS count rate model has been established using measurements in the spacecraft thermal vacuum test with the flight detector and MXS. A trade-off study using the model enables us to choose a few settings for the continuous use of the MXS optimized for different ranges of target gain tracking intervals. An alternative approach, where the MXS is used only intermittently, has also been developed and implemented. This new mode enables us to reconstruct the drift without having most of the undesirable effects in science data. This also forms the basis of the gain tracking under the current Resolve configuration with the closed gate valve.

Astronomy and AstroPhysics↗

General-Purpose Heat Source Radioisotope Thermoelectric Generator Flight Unit 5 Refurbished (GPHS-RTG F5R) Electrically Heated Thermal Vacuum Testing

Idaho National Laboratory (INL) has been tasked with the evaluation and refurbishment of the General Purpose Heat Source (GPHS) Radioisotope Thermoelectric Generator (RTG) Flight Unit 5 (GPHS-RTG F5R or F5R) that was defueled in 2005. This paper describes the testing of F5R in the thermal vacuum chamber and evaluation of the data demonstrating the generator meets updated Cassini-Huygens requirements. The generator produced 260 We of power at the specified 4100 Wth heat source inventory. This power exceeded the power requirement for 250 We , confirming system integrity and demonstrating that the generator is capable of potential NASA missions.

30 - DIRECT ENERGY CONVERSION↗

Nitric oxide molecular tagging velocimetry of a free-flight model in a reflected shock tunnel

Nitric oxide molecular tagging velocimetry (NO MTV) is used to characterize the wake behind a free-flight spherical model in the test section of a free-piston reflected shock tunnel using a burst-mode laser operated at 100 kHz. A novel (to our knowledge) multi-delay timing scheme was implemented to measure velocity in a varying collisional environment in the wake of the free-flight model. Four simultaneous velocity profiles were measured in the wake of the model from -600 to 3600 m/s for flow enthalpies of 10.3 and 12.0 MJ/kg. Finally, the measured velocity distributions show good agreement when compared to computational fluid dynamics (CFD) modeling.

47 OTHER INSTRUMENTATION↗

Drone Fleet Summary: NNLEMS UxS Rolodex entry for Sandia

Sandia’s UAS Aviation Operations Unit (UAOU) was established in 2019 to be the single entity at Sandia conducting UAS Ops in support the labs Uncrewed Aircraft Systems (UAS) activities. The UAOU currently consists of >330 FAA Registered UAS with a large variety of primarily Class 1&2 UAS: fixed wing (>90), multi-rotor (>230), hybrids, VTOLs, jets, and balloons. Many of these are threat vehicles presented as targets to Counter-UAS (CUAS) systems as part of performance tests, with the remainder in support of other projects across Sandia often with custom payload needs. The UAOU has ~15 primary pilots and reach back to another ~45 FAA Certified Remote Pilots across Sandia. The team conducts flight and CUAS operations at many test locations, including OCONUS. Sandia was awarded the 2024 DOE Federal Aviation Safety Program Award.

42 ENGINEERING↗

UAS remote sensing (Osprey platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance, Seward Peninsula, Alaska, 2018

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group. This package includes data from 34 flights flown over the NGEE-Arctic Council Mile Maker 72 (MM72), Kougarok MM64, Kougarok MM80, and Teller MM27 sites in July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. This package provide the Level 0 (raw, unprocessed) data collected by the Osprey platform. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), tabular (*.dat, *.csv, *.waypoint), and image (*.jpg) formats. This metadata document contains flight campaign, instrument and file metadata, along with a description of the L0 data, and file naming scheme. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗