Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “parameter space exploration”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28

Ion Beam Propulsion Study

The Ion Beam Propulsion Study was a joint high-level study between the Applied Physics Laboratory operated by NASA and ASRC Aerospace at Kennedy Space Center, Florida, and Berkeley Scientific, Berkeley, California. The results were promising and suggested that work should continue if future funding becomes available. The application of ion thrusters for spacecraft propulsion is limited to quite modest ion sources with similarly modest ion beam parameters because of the mass penalty associated with the ion source and its power supply system. Also, the ion source technology has not been able to provide very high-power ion beams. Small ion beam propulsion systems were used with considerable success. Ion propulsion systems brought into practice use an onboard ion source to form an energetic ion beam, typically Xe+ ions, as the propellant. Such systems were used for steering and correction of telecommunication satellites and as the main thruster for the Deep Space 1 demonstration mission. In recent years, "giant" ion sources were developed for the controlled-fusion research effort worldwide, with beam parameters many orders of magnitude greater than the tiny ones of conventional space thruster application. The advent of such huge ion beam sources and the need for advanced propulsion systems for exploration of the solar system suggest a fresh look at ion beam propulsion, now with the giant fusion sources in mind.

Source record↗

Development of a Mars Environmental Control and Life Support System (ECLSS).

ECLS systems for very long-duration human missions to Mars will be designed to operate reliably for many years and will never be returned to Earth. The need for high reliability is driven by unsympathetic abort scenarios. Abort from a Mars mission could be as long as 450 days to return to Earth. Simply put, the goal of an ECLSS is to duplicate the functions the Earth provides in terms of human living and working on our home planet but without the benefit of the Earth's large buffers - the atmospheres, the oceans and land masses. With small buffers a space-based ECLSS must operate as a true dynamic system rather than independent processors taking things from tanks, processing them, and then returning them to product tanks. Key is a development process that allows for a logical sequence of validating successful development (maturation) in a stepwise manner with key performance parameters (KPPs) at each step; especially KPPs for technologies evaluated in a full systems context with human crews on Earth and on space platforms such as the ISS. This paper will explore the implications of such an approach to ECLSS development and the roles of ground and space-based testing necessary to develop a highly reliable life support system for long duration human exploration missions. Historical development and testing of ECLS systems from Mercury to the International Space Station (ISS) will be reviewed. Current work as well as recommendations for future work will be described.

Henninger, Donald L.↗

Environmental Effects on Long Term Displacement Data of Woven Fabric Webbings Under Constant Load for Inflatable Structures

An experimental study of the effects of environmental temperature and humidity conditions on long-term creep displacement data of high strength Kevlar and VectranTM woven fabric webbings under constant load for inflatable structures is presented. The restraint layer of an inflatable structure for long-duration space exploration missions is designed to bear load and consists of an assembly of high strength webbings. Long-term creep displacement data of webbings can be utilized by designers to validate service life parameters of restraint layers of inflatable structures. Five groups of high-strength webbings were researched over a two year period. Each group had a unique webbing length, load rating, applied load, and test period. The five groups consisted of 1.) 6K Vectran webbings loaded to 49% ultimate tensile strength (UTS), 2.) 6K Vectran webbings loaded to 55% UTS, 3.) 12.5K Vectran webbings loaded to 22% UTS, 4.) 6K Kevlar webbings loaded to 40% and 43% UTS, and 5.) 6K Kevlar webbings loaded to 48% UTS. Results show that all webbing groups exhibit the initial two stages of three of a typical creep curve of an elastic material. Results also show that webbings exhibit unique local wave patterns over the duration of the test period. Data indicate that the local pattern is primarily generated by daily variations in relative humidity values within the test facility. Data indicate that after a three to six month period, where webbings reach a steady-state creep condition, an annual sinusoidal displacement pattern is exhibited, primarily due to variations in annual mean temperature values. Data indicates that variations in daily temperature values and annual mean humidity values have limited secondary effects on creep displacement behavior. Results show that webbings in groups 2 and 5 do not exhibit well defined annual displacement patterns because the magnitude of the applied loads cause large deformations, and data indicate that material yielding within a webbing tends to neutralize the annual sinusoidal displacement pattern. Study indicates that applied load, environmental effects, mechanical strength, coefficient of thermal expansion, and hygroscopic properties of webbings are fundamental requirements for quantifying accurate creep displacements and behaviors over multiple year time periods. Results from a study of the environmental effects on long-term creep displacement data of Kevlar and Vectran woven webbings are presented to increase the knowledge base of webbing materials and to enhance designs of inflatable space structures for long-duration space missions.

Kenner, WInfred S.↗

Implementing Badhwar-O'Neill Galactic Cosmic Ray Model for the Analysis of Space Radiation Exposure

For the analysis of radiation risks to astronauts and planning exploratory space missions, accurate energy spectrum of galactic cosmic radiation (GCR) is necessary. Characterization of the ionizing radiation environment is challenging because the interplanetary plasma and radiation fields are modulated by solar disturbances and the radiation doses received by astronauts in interplanetary space are likewise influenced. A model of the Badhwar‐O'Neill 2011 (BO11) GCR environment, which is represented by GCR deceleration potential theta, has been derived by utilizing all of the GCR measurements from balloons, satellites, and the newer NASA Advanced Composition Explorer (ACE). In the BO11 model, the solar modulation level is derived from the mean international sunspot numbers with time‐delay, which has been calibrated with actual flight instrument measurements to produce better GCR flux data fit during solar minima. GCR fluxes provided by the BO11 model were compared with various spacecraft measurements at 1 AU, and further comparisons were made for the tissue equivalent proportional counters measurements at low Earth orbits using the high‐charge and energy transport (HZETRN) code and various GCR models. For the comparison of the absorbed dose and dose equivalent calculations with the measurements by Radiation Assessment Detector (RAD) at Gale crater on Mars, the intensities and energies of GCR entering the heliosphere were calculated by using the BO11 model, which accounts for time‐dependent attenuation of the local interstellar spectrum of each element. The BO11 model, which has emphasized for the last 24 solar minima, showed in relatively good agreement with the RAD data for the first 200 sols, but it was resulted in to be less well during near the solar maximum of solar cycle 24 due to subtleties in the changing heliospheric conditions. By performing the error analysis of the BO11 model and the optimization in reducing overall uncertainty, the resultant BO13 model corrects the fit at solar maxima as well as being accurate at solar minima. The BO13 model is implemented to the NASA Space Cancer Risk model for the assessment of radiation risks. Overall cumulative probability distribution of solar modulation parameters represents the percentile rank of the average interplanetary GCR environment, and the probabilistic radiation risks can be assessed for various levels of GCR environment to support mission design and operational planning for future manned space exploration missions.

Kim, Myung-Hee Y.↗

Evaluating the Efficacy of Conditional Variational Autoencoders in Generating Synthetic Single Nuclei RNA-Seq Data for Space Biology Research

Astronauts are subject to unique stressors during spaceflight, leading to changes in their cellular function. However, neither astronauts nor model organisms respond the same to spaceflight, and research implicates a contribution of omics components in differential responses. Understanding how gene expression affects astronaut health is critical for the success of long-term space missions, prompting interest in developing personalized predictive models leveraging artificial intelligence (AI) and machine learning (ML) techniques. Developing such models requires extensive data, which is challenging to obtain and share. This study explores the use of conditional variational autoencoders (CVAEs) to synthetically generate single-nuclei RNA-seq (snRNA-seq) data. CVAEs build on standard variational autoencoders (VAEs) by conditioning data generation on covariates like sample identity and mission parameters, enhancing the relevance of generated data for specific contexts. For our work, we built two CVAEs with varying degrees of sparsity to optimize both interpretability and generative power. We train and validate models on existing snRNA-seq data collected from the brain tissue of mice subjected to spaceflight conditions and their ground control counterparts. We evaluate model performance using statistical tests and visualizations to compare synthetic data to real data. We aim to demonstrate that these prototype CVAE architectures could be used in future space biology work and that this is a method worth further exploring.

Sarah Golts↗

Feasibility of DEIM for retrieving the initial field via dimensionality reduction

When parameter estimation is solved in a high-dimensional space, the dimensionality reduction strategy becomes the primary consideration for alleviating the tremendous computational cost. Here, the discrete empirical interpolation method (DEIM) is explored to retrieve the initial condition (IC) by combining the polynomial chaos (PC) based ensemble Kalman filter (i.e. PC-EnKF), where a non-intrusive PC expansion is considered as a surrogate model in place of the forward model in the prediction step of the ensemble Kalman filter, resulting in fewer forward model integrations but with a comparable accuracy as Monte Carlo-based approaches. The DEIM acts as a hyper-reduction tool to provide the low-dimensional input for the high-dimensional initial field, which can be reconstructed using the information on the sparse interpolation grid points that is adaptively obtained through PC-EnKF data assimilation method. Thus an innovative framework to reconstruct the IC is developed. The detailed procedure at each assimilation iteration includes: the determination of the spatial interpolation points, the estimation of the initial values on the interpolation locations using the optimal observations, and the reconstruction of IC in the full space. The current study uses the reconstruction field of initial conditions of the Navier-Stokes equations as an example to illustrate the efficacy of our method. The experimental results demonstrate the proposed algorithm achieves a satisfactory reconstruction for the initial field. The proposed method helps to extend the applicable area of DEIM in solving inverse problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modeling Transverse Space Charge effects in IOTA with pyORBIT

The role and mitigation of space charge effects are important aspects of the beam physics research to be performed at the Integrable Optics Test Accelerator (IOTA) at Fermilab. The impact of nonlinear integrability (partial and complete) on space charge driven incoherent and coherent resonances will be a new feature of this accelerator and has the potential to influence the design of future low energy proton synchrotrons. In this report we model transverse space charge effects using the PIC code pyORBIT. First we benchmark the single particle tracking results against MADX with checks on symplecticity, tune footprints, and dynamic aperture in a partially integrable lattice realized with a special octupole string insert. Our space charge calculations begin with an examination of the 4D symplecticity. Short term tracking is done first with the initial bare lattice and then with a matching of the rms values with space charge. Next, we explore slow initialization of charge as a technique to establish steady state and reduce emittance growth and beam loss following injection into a mismatched lattice. We establish values of space charge simulation parameters so as to ensure numerical convergence. Finally, we compare the simulated space charge induced tune shifts and footprints against theory.

43 PARTICLE ACCELERATORS↗

Observations of the Bright Star in the Globular Cluster 47 Tucanae (NGC 104)

The Bright Star in the globular cluster 47 Tucanae (NGC 104) is a post-asymptotic giant branch (post-AGB) star of spectral type B8 III. The ultraviolet spectra of late-B stars exhibit myriad absorption features, many due to species unobservable from the ground. The Bright Star thus represents a unique window into the chemistry of 47 Tuc. We have analyzed observations obtained with the Far Ultraviolet Spectroscopic Explorer, the Cosmic Origins Spectrograph aboard the Hubble Space Telescope, and the Magellan Inamori Kyocera Echelle Spectrograph on the Magellan Telescope. By fitting these data with synthetic spectra, we determine various stellar parameters (T {sub eff} = 10,850 ± 250 K, logg=2.20±0.13) and the photospheric abundances of 26 elements, including Ne, P, Cl, Ga, Pd, In, Sn, Hg, and Pb, which have not previously been published for this cluster. Abundances of intermediate-mass elements (Mg through Ga) generally scale with Fe, while the heaviest elements (Pd through Pb) have roughly solar abundances. Its low C/O ratio indicates that the star did not undergo third dredge-up and suggests that its heavy elements were made by a previous generation of stars. If so, this pattern should be present throughout the cluster, not just in this star. Stellar-evolution models suggest that the Bright Star is powered by a He-burning shell, having left the AGB during or immediately after a thermal pulse. Its mass (0.54 ± 0.16M {sub ⊙}) implies that single stars in 47 Tuc lose 0.1–0.2 M {sub ⊙} on the AGB, only slightly less than they lose on the red giant branch.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Jet Noise Diagnostics Supporting Statistical Noise Prediction Methods

The primary focus of my presentation is the development of the jet noise prediction code JeNo with most examples coming from the experimental work that drove the theoretical development and validation. JeNo is a statistical jet noise prediction code, based upon the Lilley acoustic analogy. Our approach uses time-average 2-D or 3-D mean and turbulent statistics of the flow as input. The output is source distributions and spectral directivity. NASA has been investing in development of statistical jet noise prediction tools because these seem to fit the middle ground that allows enough flexibility and fidelity for jet noise source diagnostics while having reasonable computational requirements. These tools rely on Reynolds-averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) solutions as input for computing far-field spectral directivity using an acoustic analogy. There are many ways acoustic analogies can be created, each with a series of assumptions and models, many often taken unknowingly. And the resulting prediction can be easily reverse-engineered by altering the models contained within. However, only an approach which is mathematically sound, with assumptions validated and modeled quantities checked against direct measurement will give consistently correct answers. Many quantities are modeled in acoustic analogies precisely because they have been impossible to measure or calculate, making this requirement a difficult task. The NASA team has spent considerable effort identifying all the assumptions and models used to take the Navier-Stokes equations to the point of a statistical calculation via an acoustic analogy very similar to that proposed by Lilley. Assumptions have been identified and experiments have been developed to test these assumptions. In some cases this has resulted in assumptions being changed. Beginning with the CFD used as input to the acoustic analogy, models for turbulence closure used in RANS CFD codes have been explored and compared against measurements of mean and rms velocity statistics over a range of jet speeds and temperatures. Models for flow parameters used in the acoustic analogy, most notably the space-time correlations of velocity, have been compared against direct measurements, and modified to better fit the observed data. These measurements have been extremely challenging for hot, high speed jets, and represent a sizeable investment in instrumentation development. As an intermediate check that the analysis is predicting the physics intended, phased arrays have been employed to measure source distributions for a wide range of jet cases. And finally, careful far-field spectral directivity measurements have been taken for final validation of the prediction code. Examples of each of these experimental efforts will be presented. The main result of these efforts is a noise prediction code, named JeNo, which is in middevelopment. JeNo is able to consistently predict spectral directivity, including aft angle directivity, for subsonic cold jets of most geometries. Current development on JeNo is focused on extending its capability to hot jets, requiring inclusion of a previously neglected second source associated with thermal fluctuations. A secondary result of the intensive experimentation is the archiving of various flow statistics applicable to other acoustic analogies and to development of time-resolved prediction methods. These will be of lasting value as we look ahead at future challenges to the aeroacoustic experimentalist.

Bridges, James E.↗

Design Space Exploration of Emerging Memory Technologies for Machine Learning Applications

Memory design space exploration methods study memory systems’ performances and limitations before implementation. The computer memory design space has grown exponentially because of the enormous growth of memory types, memory controllers, and application software. Computer simulators are commonly used for memory design space exploration. However, complex memory simulations take an enormous amount of time. Hence, in this paper, we proposed a machine learning-based design space exploration method for dynamic random-access memory and non-volatile memory systems. We applied our method to the CosmoGAN and LeNet applications to predict the following six memory response parameters: (i) bandwidth, (ii) power, (iii) average latency, (iv) average total latency, (v) memory reads, and (vi) memory writes. Our experimental results show that machine learning models can predict memory response parameter values faster than simulations. We used support vector machine, random forest, and gradient boosting machine learning models. We observed that the support vector machine provides better performance for bandwidth, average latency, and average total latency. The random forest model works better for memory reads and writes. The gradient boosting model provides superior prediction performance for power. We provide a detailed discussion on learning curve characteristics, error analysis, and memory type recommendation.

Hasan, S M Shamimul↗

Proposal for a proton-bunch compression experiment at IOTA in the strong space-charge regime

The longitudinal compression of intense proton bunches with strong space-charge force is an essential component of a proton-based muon source for a muon collider. This paper discusses a proton-bunch compression experiment at the Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab to explore optimal radio frequency (RF) cavity and lattice configurations. IOTA is a compact fixed-energy storage ring that can circulate a 2.5-MeV proton beam with varying beam parameters and lattice configurations. The study will aim to demonstrate a bunch-compression factor of at least 2 in the IOTA ring while examining the impact of intense space-charge effects on the compression process.

43 PARTICLE ACCELERATORS↗

Proposal for a Proton-Bunch Compression Experiment at IOTA in the Strong Space-Charge Regime

The longitudinal compression of intense proton bunches with strong space-charge force is an essential component of a proton-based muon source for a muon collider. This paper discusses a proton-bunch compression experiment at the Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab to explore optimal radio frequency (RF) cavity and lattice configurations. IOTA is a compact fixed-energy storage ring that can circulate a 2.5-MeV proton beam with varying beam parameters and lattice configurations. The study will aim to demonstrate a bunch-compression factor of at least 2 in the IOTA ring while examining the impact of intense space-charge effects on the compression process.

43 PARTICLE ACCELERATORS↗

Morphologic Parameters for Successful Lunar Landing Sites

The Moon, with its abundant resources, intriguing science questions, and vast unexplored surface area, is the most attainable and useful near-term target for future human exploration. In recognition of this fact, Presidential Space Policy Directive 1 (PSPD-1) has directed the United States to return to the Moon for “long-term exploration and utilization”, beginning with the 7th American human lunar landing by 2024 and building to sustainable surface presence by 2028.

Lawrence, S. J.↗

Space Life Sciences at NASA: Spaceflight Health Policy and Standards

In January 2005, the President proposed a new initiative, the Vision for Space Exploration. To accomplish the goals within the vision for space exploration, physicians and researchers at Johnson Space Center are establishing spaceflight health standards. These standards include fitness for duty criteria (FFD), permissible exposure limits (PELs), and permissible outcome limits (POLs). POLs delineate an acceptable maximum decrement or change in a physiological or behavioral parameter, as the result of exposure to the space environment. For example cardiovascular fitness for duty standards might be a measurable clinical parameter minimum that allows successful performance of all required duties. An example of a permissible exposure limit for radiation might be the quantifiable limit of exposure over a given length of time (e.g. life time radiation exposure). An example of a permissible outcome limit might be the length of microgravity exposure that would minimize bone loss. The purpose of spaceflight health standards is to promote operational and vehicle design requirements, aid in medical decision making during space missions, and guide the development of countermeasures. Standards will be based on scientific and clinical evidence including research findings, lessons learned from previous space missions, studies conducted in space analog environments, current standards of medical practices, risk management data, and expert recommendations. To focus the research community on the needs for exploration missions, NASA has developed the Bioastronautics Roadmap. The Bioastronautics Roadmap, NASA's approach to identification of risks to human space flight, revised baseline was released in February 2005. This document was reviewed by the Institute of Medicine in November 2004 and the final report was received in October 2005. The roadmap defines the most important research and operational needs that will be used to set policy, standards (define acceptable risk), and implement an overall Risk Management and Analysis process. Currently NASA is drafting spaceflight health standards for neurosensory alterations, space radiation exposure, behavioral health, muscle atrophy, cardiovascular fitness, immunological compromise, bone demineralization, and nutrition.

Davis, Jeffrey R.↗

Current and Future γ-Ray Searches for Dark Matter Annihilation Beyond the Unitarity Limit

For decades, searches for electroweak-scale dark matter (DM) have been performed without a definitive detection. This lack of success may hint that DM searches have focused on the wrong mass range. A proposed candidate beyond the canonical parameter space is ultraheavy DM (UHDM). In this work, we consider indirect UHDM annihilation searches for masses between 30 TeV and 30 PeV—extending well beyond the unitarity limit at ~100 TeV—and discuss the basic requirements for DM models in this regime. We explore the feasibility of detecting the annihilation signature, and the expected reach for UHDM with current and future very-high-energy (VHE; >100 GeV) γ-ray observatories. Specifically, we focus on three reference instruments: two Imaging Atmospheric Cherenkov Telescope arrays, modeled on VERITAS and CTA-North, and one extended air shower array, motivated by HAWC. With reasonable assumptions on the instrument response functions and background rate, we find a set of UHDM parameters (mass and cross section) for which a γ-ray signature can be detected by the aforementioned observatories. Here, we further compute the expected upper limits for each experiment. With realistic exposure times, the three instruments can probe DM across a wide mass range. At the lower end, it can still have a point-like cross section, while at higher masses the DM could have a geometric cross section, indicative of compositeness.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

In-Situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori ground-truth labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and auxiliary (e.g. trajectory) data and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our misclassification rates as related to our ground-truth labels, and with multi-layered pollution plume cases. The next step in our analysis is to optimize parameter selection for a scheme that can be applied to space-borne aerosol and trace-gas observation platforms such as OMI, and future geostationary satellites such as TEMPO and GEO-CAPE.

Neural-network↗

Sensor-Web Operations Explorer

Understanding the atmospheric state and its impact on air quality requires observations of trace gases, aerosols, clouds, and physical parameters across temporal and spatial scales that range from minutes to days and from meters to more than 10,000 kilometers. Observations include continuous local monitoring for particle formation; field campaigns for emissions, local transport, and chemistry; and periodic global measurements for continental transport and chemistry. Understanding includes global data assimilation framework capable of hierarchical coupling, dynamic integration of chemical data and atmospheric models, and feedback loops between models and observations. The objective of the sensor-web system is to observe trace gases, aerosols, clouds, and physical parameters, an integrated observation infrastructure composed of space-borne, air-borne, and in-situ sensors will be simulated based on their measurement physics properties. The objective of the sensor-web operation is to optimally plan for heterogeneous multiple sensors, the sampling strategies will be explored and science impact will be analyzed based on comprehensive modeling of atmospheric phenomena including convection, transport, and chemical process. Topics include system architecture, software architecture, hardware architecture, process flow, technology infusion, challenges, and future direction.

observation↗

Geophysical Observations of the 2023 September 24 OSIRIS-REx Sample Return Capsule Reentry

Sample return capsules (SRCs) entering Earth's atmosphere at hypervelocity from interplanetary space are a valuable resource for studying meteor phenomena. The 2023 September 24 arrival of the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer SRC provided an unprecedented chance for geophysical observations of a well-characterized source with known parameters, including timing and trajectory. A collaborative effort involving researchers from 16 institutions executed a carefully planned geophysical observational campaign at strategically chosen locations, deploying over 400 ground-based sensors encompassing infrasound, seismic, distributed acoustic sensing, and Global Positioning System technologies. Additionally, balloons equipped with infrasound sensors were launched to capture signals at higher altitudes. This campaign (the largest of its kind so far) yielded a wealth of invaluable data anticipated to fuel scientific inquiry for years to come. The success of the observational campaign is evidenced by the near-universal detection of signals across instruments, both proximal and distal. This paper presents a comprehensive overview of the collective scientific effort, field deployment, and preliminary findings. The early findings have the potential to inform future space missions and terrestrial campaigns, contributing to our understanding of meteoroid interactions with planetary atmospheres. Furthermore, the data set collected during this campaign will improve entry and propagation models and augment the study of atmospheric dynamics and shock phenomena generated by meteoroids and similar sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗