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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Improving ICARUS Track Reconstruction Algorithms

The ICARUS experiment is part of the Short-Baseline Neutrino (SBN) program at Fermilab. The main goal of the experiment is to investigate the possibility of sterile neutrinos in the O(1 eV) mass region and provide clarification of the anomaly detected from the Liquid Scintillator Neutrino Detector (LSND) and MiniBooNE experiments. The ICARUS-T600 detector is a Liquid Argon Time Projection Chamber (LAr-TPC), that can provide excellent 3D imaging and calorimetric reconstruction of any ionizing particles. This detection technique allows a detailed study of neutrino interactions, spanning a wide energy spectrum (from a few keV to several hundreds of GeV). The detector consists of two identical adjacent modules, filled with a total of 760 tons of ultra-pure liquid argon. Each module houses two LAr-TPCs separated by a common cathode with a maximum drift distance of 1.5 m, equivalent to about 1 ms drift time for the nominal $500$ V/m electric drift field. The anode is made of three parallel wire planes positioned 3 mm apart, where the stainless-steel wires are oriented on each plane at a different angle with respect to the horizontal direction ($+60^\degree$,$-60^\degree$,$0^\degree$). The first two planes (Induction 1 and Induction 2) provide a non-destructive charge measurement, whereas the ionization charge is fully collected by the last collection plane. In total, 53248 wires with a 3 mm pitch and length up to 9 m are installed in the detector. In the first stage of the reconstruction, segments of waveforms corresponding to physical signals (hits) are searched for in the deconvolved wire waveform with a threshold-based hit-finding algorithm. Each hit is then fitted with a Gaussian, whose area is proportional to the number of drift electrons generating the signal. In the second stage of the reconstruction, hits are passed as input to Pandora, a framework software composed of different pattern recognition algorithms, that performs a 3D reconstruction of the full image recorded in the collected event, including the identification of interaction vertices and tracks and showers inside the TPC. These are organized into a hierarchical structure (called slice) of particles generated starting from a primary interaction vertex. In some cases, related to the inefficiencies in the hit detection or excessive deflection of the particle trajectory, Pandora breaks the particle's track into two or more smaller pieces and considers each piece as an independent track. We studied this phenomenon focusing on primary muons from ν_μ CC interactions contained in a single module with a track at least 20 cm long, to exclude delta rays. The study determined that about $7-8\%$ of the muon tracks are broken. Approximately $80\%$ of the times, Pandora assigns all segments of the track to the same slice (intra-slice track split), while in the remaining $20\%$ of the cases, one of the segments is associated with another slice (extra-slice track split). To mitigate this phenomenon, we designed an algorithm that detects and stitches the tracks broken by Pandora for the intra-slice split. In Monte Carlo simulations, the algorithm showed an efficiency exceeding $80\%$ and a purity exceeding $93\%$.

Ricci, Alessandro Maria [Pisa U.; INFN, Pisa] (ORC↗
NASA NTRS2002

Model predictions and visualization of the particle flux on the surface of Mars

Model calculations of the particle flux on the surface of Mars due to the Galactic Cosmic Rays (GCR) can provide guidance on radiobiological research and shielding design studies in support of Mars exploration science objectives. Particle flux calculations for protons, helium ions, and heavy ions are reported for solar minimum and solar maximum conditions. These flux calculations include a description of the altitude variations on the Martian surface using the data obtained by the Mars Global Surveyor (MGS) mission with its Mars Orbiter Laser Altimeter (MOLA) instrument. These particle flux calculations are then used to estimate the average particle hits per cell at various organ depths of a human body in a conceptual shelter vehicle. The estimated particle hits by protons for an average location at skin depth on the Martian surface are about 10 to 100 particle-hits/cell/year and the particle hits by heavy ions are estimated to be 0.001 to 0.01 particle-hits/cell/year.

NASA Center JSC↗
DOE OSTI2022

GNN-based end-to-end reconstruction in the CMS Phase 2 High-Granularity Calorimeter

We present the current stage of research progress towards a one-pass, completely Machine Learning (ML) based imaging calorimeter reconstruction. The model used is based on Graph Neural Networks (GNNs) and directly analyzes the hits in each HGCAL endcap. The ML algorithm is trained to predict clusters of hits originating from the same incident particle by labeling the hits with the same cluster index. We impose simple criteria to assess whether the hits associated as a cluster by the prediction are matched to those hits resulting from any particular individual incident particles. The algorithm is studied by simulating two tau leptons in each of the two HGCAL endcaps, where each tau may decay according to its measured standard model branching probabilities. The simulation includes the material interaction of the tau decay products which may create additional particles incident upon the calorimeter. Using this varied multiparticle environment we can investigate the application of this reconstruction technique and begin to characterize energy containment and performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Cache management based on access type priority

Systems, apparatuses, and methods for cache management based on access type priority are disclosed. A system includes at least a processor and a cache. During a program execution phase, certain access types are more likely to cause demand hits in the cache than others. Demand hits are load and store hits to the cache. A run-time profiling mechanism is employed to find which access types are more likely to cause demand hits. Based on the profiling results, the cache lines that will likely be accessed in the future are retained based on their most recent access type. The goal is to increase demand hits and thereby improve system performance. An efficient cache replacement policy can potentially reduce redundant data movement, thereby improving system performance and reducing energy consumption.

Yin, Jieming↗
DOE OSTI2024

NuGraph2: A Graph Neural Network for Neutrino Event Reconstruction

Neutrino experiments are set to probe some of the most important open questions in physics, from CP violation and the nature of dark matter. The technology of choice for many of these experiments is the liquid argon time projection chamber (LArTPC). In current LArTPC experiments, reconstruction performance often represents a limiting factor for the sensitivity. New developments are therefore needed to unlock the full potential of LArTPC experiments. NuGraph2 is a state of the art Graph Neural Network for reconstruction of data in LArTPC experiments. NuGraph2 utilizes a heterogeneous graph structure, with separate subgraphs of 2D nodes (hits in each plane) connected across planes via 3D nodes (space points). The model provides a consistent description of the neutrino interaction across all planes. NuGraph2 is a multi-purpose network, with a common message-passing attention engine connected to multiple decoders with different classification or regression tasks. These include the classification of detector hits according to the particle type that produced them (semantic segmentation) and the separation of hits from the neutrino interaction from hits due to noise or cosmic-ray background. Additional decoders are being developed, performing tasks such as the regression of the neutrino interaction vertex position. Performance results will be presented based on publicly available samples from MicroBooNE. These include both physics performance metrics, achieving 95% accuracy for semantic segmentation and 98% classification of neutrino hits, as well as computational metrics for training and for inference on CPU or GPU. The status of the NuGraph integration in the LArSoft software framework will be presented, as well as initial studies about model interpretability and injection of domain knowledge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

NuGraph2: A Graph Neural Network for Neutrino Event Reconstruction

Neutrino experiments are set to probe some of the most important open questions in physics, from CP violation and the nature of dark matter. The technology of choice for many of these experiments is the liquid argon time projection chamber (LArTPC). In current LArTPC experiments, reconstruction performance often represents a limiting factor for the sensitivity. New developments are therefore needed to unlock the full potential of LArTPC experiments. NuGraph2 is a state of the art Graph Neural Network for reconstruction of data in LArTPC experiments [https://arxiv.org/abs/2403.11872]. NuGraph2 utilizes a heterogeneous graph structure, with separate subgraphs of 2D nodes (hits in each plane) connected across planes via 3D nodes (space points). The model provides a consistent description of the neutrino interaction across all planes. NuGraph2 is a multi-purpose network, with a common message-passing attention engine connected to multiple decoders with different classification or regression tasks. These include the classification of detector hits according to the particle type that produced them (semantic segmentation) and the separation of hits from the neutrino interaction from hits due to noise or cosmic-ray background. Additional decoders are being developed, performing tasks such as the regression of the neutrino interaction vertex position. Performance results will be presented based on publicly available samples from MicroBooNE. These include both physics performance metrics, achieving 95% accuracy for semantic segmentation and 98% classification of neutrino hits, as well as computational metrics for training and for inference on CPU or GPU. The status of the NuGraph integration in the LArSoft software framework will be presented, as well as initial studies about model interpretability and injection of domain knowledge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

De-noising drift chambers in CLAS12 using convolutional auto encoders

Modern Nuclear Physics experimental setups run experiments with higher beam intensity resulting in increased noise in detector components used for particle track reconstruction. Increased uncorrelated signals (noise) result in decreased particle reconstruction efficiency. In this paper, we investigate the usage of Machine Learning, specifically Convolutional Neural Network Auto-Encoders (CAE), for de-noising raw hits from drift chambers in the CLAS12 detector. To the best of our knowledge, this is the first time CAE is employed to perform such an operation in this field. During the de-noising phase, it is important to remove as much noise as possible while retaining the valid hits to avoid losing crucial information about the experiment. Here, we show that using CAE, it is possible to remove noise hits while retaining up to 94% of valid tracks for a beam current of 110nA while for lower beam currents (45-55nA), we get up to 98% efficiency. Studies on experimental conditions with increasing noise show that CAE performs better than conventional tracking algorithms in isolating hits belonging to tracks. Specifically, the de-noising algorithm results in tracking efficiency improvements greater than 15%, in real data production procedures with nominal conditions, and up to two times better efficiency in synthetically generated data with high luminosity conditions (90-110nA), indicating that machine learning can lead to significantly shorter times for conducting physics experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Degradation-related defect level in weathered silicon heterojunction modules characterized by deep level transient spectroscopy

Commercial silicon heterojunction photovoltaic modules, known as amorphous-silicon-based heterojunction with intrinsic thin-film layer (HIT) modules, show average degradation after 10 years in the field. HIT modules weathered outdoors in Colorado and Florida display mostly uniform decreases in intensity when mapped with photoluminescence (PL) imaging compared to a control module. Flash-table-based current-voltage curves show that degradation is dominated by voltage loss. Samples are cored from each of the modules, and deep level transient spectroscopy (DLTS) detects three electron-trap defect states in all modules with activation energies of electron emission from the defects of 0.07, 0.16, and 0.50 eV. DLTS measurements on the weathered modules show an additional deep-level, electron-trap defect state with an activation energy of 0.51 eV and a trap density of approximately 10 12 cm –3 . The capture rate is measured using varying short filling pulse times, and the resulting capture cross section is estimated to be 1.1x10 –16 cm 2 . The development of the weathering-related defect level correlates to decreases in carrier lifetime, PL intensity, and module voltage. Various depths of the space charge region are probed with increments in applied reverse bias and filling-pulse bias. Furthermore, this DLTS depth profiling shows a trend of trap density increasing with less applied reverse bias, suggesting that the weathering-related defect increases carrier recombination toward the interface between the bulk silicon wafer and the junction-forming amorphous-silicon passivation layers.

14 SOLAR ENERGY↗
DOE OSTI2025

Light-powered end-to-end neutron detection and imaging with an edge-deployed optical AI chip

Neutron detection is widely used in many applications including nuclear physics, nuclear energy, nuclear technologies and nuclear safeguards. Developing an end-to-end neutron detection and imaging workflow paves way towards fully automated processes for many applications. We implemented an automated workflow for neutron detection experiments which use a solid state image sensor to capture neutron hits as a digital image. We deploy the workflow to an edge-based optical neural network (ONN) to increase the radiation-hardness and lifetime of neutron detection instruments. We present a two-stage neural network framework for detection of neutrons at sub-pixel resolution. The first stage uses a region proposal network to efficiently detect and extract neutron hits from the input camera image. The second stage feeds the extracted hits into a fully connected neural network to predict the sub-pixel hit position. The performance of the two-stage framework is evaluated using the edge-based ONN. The results show that we can achieve above 96% neutron detection accuracy as well as sub-pixel and sub-micron position resolution, while enjoying the advantages of the ONN hardware including radiation-hardness, low energy consumption and high computing speed for integrated edge camera and hardware deployment, when compared with electronic counterparts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers

This paper presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise for similar reconstruction tasks in the LHC. In this paper, a multihead attention message passing network is used to classify the relationship between detector hits by labelling graph edges, determining whether hits were produced by the same underlying particle, and if so, the particle type. The trained model is 84% accurate overall, and performs best on the EM shower and muon track classes. The model’s strengths and weaknesses are discussed, and plans for developing this technique further are summarised.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Deep learning-based spatiotemporal multi-event reconstruction for delay line detectors

Abstract Accurate observation of two or more particles within a very narrow time window has always been a challenge in modern physics. It creates the possibility of correlation experiments, such as the ground-breaking Hanbury Brown–Twiss experiment, leading to new physical insights. For low-energy electrons, one possibility is to use a Microchannel plate with subsequent delay lines for the readout of the incident particle hits, a setup called a Delay Line Detector. The spatial and temporal coordinates of more than one particle can be fully reconstructed outside a region called the dead radius. For interesting events, where two electrons are close in space and time, the determination of the individual positions of the electrons requires elaborate peak finding algorithms. While classical methods work well with single particle hits, they fail to identify and reconstruct events caused by multiple nearby particles. To address this challenge, we present a new spatiotemporal machine learning model to identify and reconstruct the position and time of such multi-hit particle signals. This model achieves a much better resolution for nearby particle hits compared to the classical approach, removing some of the artifacts and reducing the dead radius a factor of eight. We show that machine learning models can be effective in improving the spatiotemporal performance of delay line detectors.

Computer Science↗
DOE OSTI2023

Uncertainty Analysis of the NOvA Test Beam Wire Chambers

The Fermilab Test Beam is a beam designed for R&D for a variety of experiments taking place at Fermilab, for instance the NOvA experiment. An essential component of the NOvA Test Beam is four wire chambers which measure the transverse position of particles travelling along the beamline. Occasionally, a particle will not produce a hit in one of the four wire chambers resulting in a “3 hit track” instead of the usual “4 hit track”. In our research, we explored the possibility of including these 3 hit tracks into analysis, and how they impact relevant statistics.

Scheuermann, Elizabeth↗
DOE OSTI2024

Electron Density Measurements Using USPR (Final Scientific/Technical Report)

UC Davis has fabricated an ultrashort pulse reflectometer (USPR) diagnostic instrument for electron density profile measurements on compact, short duration, magnetically-confined fusion-energy concept devices such as spheromaks and FRCs. The USPR system transmits extremely short duration (~few nsec) chirped waveforms that together span 29 to 75 GHz. These chirped waveforms illuminate and reflect from the target plasma, with each frequency component reflecting from a different density layer (higher frequencies probe deeper into the plasma before reflecting). The reflected waveforms are split into roughly 42 different frequencies; time-of-flight (TOF) measurements made at each frequency with high resolution (~25 psec measurement resolution which corresponds to ~5 mm). These TOF data may then be inverted via software to generate electron density profiles with high time resolution (~10 μsec). At the heart of the system is a field programmable gate array (FPGA) based controller which collects and processes all of the USPR data in addition to generating all of the control signals required for maximum flexibility. The FPGA controller has the software flexibility to be easily reconfigured for different plasma devices, and the entire system sufficiently compact to be easily and quickly transported between devices. A high speed impulse generator was transformed into a set of three ultrashort pulse transmitter chirps using a combination of dispersive waveguide, frequency doublers and high-pass filters. A mm-wave controller was fabricated to sequentially switch between the three chirps, directing the chirps one-by-one to three different mm-wave assemblies spanning 29-75 GHz. Each mm-wave assembly consists of a high power active multiplier chain which converts the transmitter chirp to higher frequencies, and a broadband mixer which downconverts the reflected waveform to the 2-18 GHz range of the UPSR receiver. The 16-channel receiver (shared by all 3 mm-wave assemblies) was fabricated employing custom TOF modules capable of operating at a high 1 MHz sampling rate. Laboratory testing of the full system revealed the presence of unwanted harmonics from the multiplication process, with interference observed in the downconverted reflections at selected frequency channels that could not be completely filtered out. Additional interference effects arising from internal reflections within the mm-wave assemblies were minimized using a high-speed switch which served to “gate out” much of these reflections. The USPR diagnostic was transported and installed onto the HIT-SIU plasma device, becoming operational on 11/08/2022. Although designed to span 3 distinct mm-wave bands, the HIT-SIU plasmas at this time were sufficiently low density such that only the lowest of the three bands was likely to have strong plasma reflections. The system was then set to operate on only the lowest band (assembly #1), with data collected every 1 μsec rather than 3 μsec which would have been the case when cycling through all three bands. Connected to HIT-SIU, time-varying plasma reflections were observed on 9 of 16 possible frequency channels. Close examination of the data collected revealed issues previously unobserved in laboratory testing, associated with (a) reflections from the small aperture horns required for operation within the HIT-SIU device, and (b) a dependence of the recorded TOF with the threshold voltage of a given channel. Plans were made to address each of these issues before undertaking any future campaigns.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Intrabasin Comparison of Produced Fluid From Hydraulically Fractured Wells in the Permian Region

The Permian Basin is the highest producing oil and gas reservoir in the United States. Hydrocarbon extraction methods in this region are often associated with frac hits, or interwell communication events where an established well is affected by the pumping of fracture fluid into a new well. Our previous work revealed a unique geochemical signal indicating the presence of frac hits in the Permian Basin. We returned to this area with the overall goal of expanding our understanding of the microbial and geochemical dynamics common in this region. To do so, we collected produced water from 25 unique sites across the Permian Basin, 10 of which had previously been characterized during an active frac hit with the rest being novel. For each sample, we measured the pH, alkalinity, geochemical composition, microbial load (qPCR), and microbial community composition (16S rRNA sequencing). Permian Basin produced water is characterized by higher sulfate and lower total dissolved solids (TDS) concentrations compared to other regions. Interestingly, wells impacted by frac hits have a geochemical profile that resembles that of fracture fluid, with both lowered sulfate and lowered TDS concentrations compared to unaffected wells in this region. Due to the year-long recovery window between sample collection periods, we anticipate that all of our data will be characterized by the typical high sulfate, low TDS concentrations.

environmental microbiology↗
DOE OSTI2025

Intrabasin Comparison of the Microbiology and Geochemistry of Produced Fluid From Hydraulically Fractured Wells in the Permian Region

The Permian Basin is the highest producing oil reservoir in the United States. Hydrocarbon extraction methods in this region are often associated with frac hits, or interwell communication events where an established well is affected by the pumping of fracture fluid into a new well. Our previous work revealed a geochemical signal indicating the presence of frac hits in the Permian Basin. We returned to this area with the goal of expanding our understanding of subsurface interactions common in this region. To do so, we collected produced water from 25 unique sites across the Permian Basin, 10 of which had previously been characterized during an active frac hit. For each sample, we measured the pH, alkalinity, geochemistry, microbial load, and microbial community composition. Permian Basin produced water is characterized by higher sulfate and lower total dissolved solids (TDS) concentrations compared to other regions. Interestingly, wells impacted by frac hits have a geochemical profile that resembles that of fracture fluid, with both lowered sulfate and lowered TDS concentrations compared to unaffected wells. Due to the year-long recovery window between sample collection periods, we anticipate that all our data will be characterized by the typical high sulfate, low TDS concentrations.

geochemistry↗
NASA NTRS1990

HgZnTe-based detectors for LWIR NASA applications

The initial goal was to grow and characterize HgZnTe and determine if it indeed had the advantageous properties that were predicted. Researchers grew both bulk and liquid phase epitaxial HgZnTe. It was determined that HgZnTe had the following properties: (1) microhardness at least 50 percent greater than HgCdTe of equivalent bandgap; (2) Hg annealing rates of at least 2 to 4 times longer than HgCdTe; and (3) higher Hg vacancy formation energies. This early work did not focus on one specific composition (x-value) of HgZnTe since NASA was interested in HgZnTe's potential for a variety of applications. Since the beginning of 1989, researchers have been concentrating, however, on the liquid phase growth of very long wavelength infrared (VLWIR) HgZnTe (cutoff approx. equals 17 microns at 65K) to address the requirements of the Earth Observing System (EOS). Since there are no device models to predict the advantages in reliability one can gain with increased microhardness, surface stability, etc., one must fabricate HgZnTe detectors and assess their relative bake stability (accelerated life test behavior) compared with HgCdTe devices fabricated in the same manner. Researchers chose to fabricate HIT detectors as a development vehicle for this program because high performance in the VLWIR has been demonstrated with HgCdTe HIT detectors and the HgCdTe HIT process should be applicable to HgZnTe. HIT detectors have a significant advantage for satellite applications since these devices dissipate much less power than conventional photoconductors to achieve the same responsivity.

Patten, Elizabeth A.↗
NASA NTRS1994

Debris/ice/TPS assessment and integrated photographic analysis for Shuttle Mission STS-62

A pre-launch debris inspection of the pad and Shuttle vehicle was conducted on 2 March 1994. The detailed walkdown of Launch Pad 39B and MLP-1 also included the primary flight elements OV-102 Columbia (16th flight), ET-62 (LWT 55), and BI-064 SRB's. There were no significant facility or vehicle anomalies. After the launch on March 4th, a debris inspection of Pad 39B was performed. Damage to the pad overall was minimal. On-orbit photographs taken by the flight crew and two films from the ET/ORB umbilical cameras of the External Tank after separation from the Orbiter revealed no major damage or lost flight hardware that would have been a safety of flight concern. Orbiter performance on final approach appeared normal. Infrared imagery of landing gear deployment showed the loss of thermal barrier from the nose gear wheel well. The missing thermal barrier material was not recovered. The Solid Rocket Boosters were inspected at Hanger AF after retrieval. Both frustums had a combined total of 44 MSA-2 debonds over fasteners. Significant amounts of BTA had been applied to closeouts on the RH frustum, forward skirt, and aft skirt. Hypalon paint was blistered/missing over the areas were the BTA had been applied. The underlying BTA was not sooted (IFA STS-62-B-1). Investigation of this condition has concluded there was insufficient heat rates to cause blistering of the Hypalon until late in the ascent phase. A post landing inspection of OV-102 was conducted after the landing at KSC. The Orbiter TPS sustained a total of 97 hits, of which 16 had a major dimension of 1 inch or larger. The Orbiter lower surface had a total of 36 hits, of which 7 had a major dimension of 1 inch or larger. Based on these numbers and comparison to statistics from previous missions of similar configuration, both the total number of debris hits and the number of hits 1 inch or larger was less than average. Six thermal barriers, total size approximately 36 in. x 3 in. x 1.5 in., and one corner tile piece 4 in. x 4 in., were missing from the nose landing gear doors. Runway infrared cameras recorded these objects falling from the Orbiter when the nose landing gear doors were opened on final approach. A search of the area under the flight path failed to recover the missing thermal batteries, which may be submerged in the large body of water south of the runway. The cause for the loss of the material was attributed to the way the substrate was prepared for bonding at the vendor. Orbiter post landing microchemical sample results revealed a variety of residuals in the Orbiter window samples. These were attributed to SRB BSM exhaust, Orbiter TPS, window protective covers and processing, natural landing site products, and paints/primers from various sources. The residual sampling data do not indicate a single source of damaging debris and all of these materials have been documented previously in analyses for post landing sample reports. Data from residual sampling also showed no trends when compared to previous mission data. A total of ten Post Launch Anomalies, including one IFA, were observed during the STS-62 mission assessment.

Katnik, Gregory N.↗
NASA NTRS1994

Single track effects, Biostack and risk assessment

The scientific career of Prof. Bucker has spanned a very exciting period in the fledgling science of Space Radiation Biology. The capability for placing biological objects in space was developed, and the methods for properly packaging, retrieving and analyzing them were worked out. Meaningful results on the effects of radiation were obtained for the first time. In fact, many of the successful techniques and methodologies for handling biological samples were developed in Prof. Bucker's laboratories, as attested by the extensive Biostack program. He was the first to suggest and successfully carry out experiments in space directly aimed at measuring effects of single tracks of high-energy heavy galactic cosmic rays by specifically identifying whether or not the object had been hit by a heavy particle track. Because the "hit" frequencies of heavy galactic cosmic rays to cell nuclei in the bodies of space travelers will be low, it is expected that any effects to humans on the cellular level will be dominated by single-track cell traversals. This includes the most important generally recognized late effect of space radiation exposure: radiation-induced cancer. This paper addresses the single-track nature of the space radiation environment, and points out the importance of single "hits" in the evaluation of radiation risk for long-term missions occurring outside the earth's magnetic field. A short review is made of biological objects found to show increased effects when "hit" by a single heavy charged-particle in space. A brief discussion is given of the most provocative results from the bacterial spore Bacillus subtilis: experimental evidence that tracks can affect biological systems at much larger distances from the trajectory than previously suspected, and that the resultant inactivation cross section in space calculated for this system is very large. When taken at face value, the implication of these results, when compared to those from experiments performed at ground-based accelerators with beams at low energies in the same LET range, is that high-energy particles can exert their influence a surprising distance from their trajectory and the inactivation cross sections are some 20 times larger than expected. Clearly, beams from high-energy heavy-ion accelerators should be used to confirm these results. For those end points that can also be caused by low-LET beams such as high-energy protons, it is important to measure their action cross sections as well. The ratio of the cross sections for a high-LET beam to that of a low-LET beam is an interesting experimental ratio and, we suggest, of more intrinsic interest than the RBE (Relative Biological Effectiveness). It is a measure of the "biological" importance of one particle type relative to another particle type. This ratio will be introduced and given the name RPPE (Relative Per Particle Effectiveness). Values of RPPE have appeared in the literature and will be discussed. A rather well-known value of this quantity (13,520) has been suggested for the RPPE of high-energy iron ions to high-energy protons. This value was suggested by Letaw et al. Nature 330, 709-710 (1987)] we will call it the Letaw limit. It will be discussed in terms of the importance of the heavy-ion component vs light-ion component of the galactic cosmic rays. It is also pointed out, however, that there may be unique effects from single tracks of heavy ions that do not occur from light-ion tracks. For such effects, the concepts of both RBE and RPPE lose their meaning.

NASA Discipline Radiation Health↗