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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Computational Fluid Dynamics Simulations to Assess Spatial Variability and Optimal Ventilation Scenarios for Biological Laboratory Exposures

A significant amount of uncertainty exists regarding potential human exposure to laboratory biomaterials and organisms in Biosafety Level 2 (BSL-2) research laboratories. Computational fluid dynamics (CFD) modeling is proposed as a way to better understand potential impacts of different combinations of biomaterials, laboratory manipulations, and exposure routes on risks to laboratory workers. Here, in this study, we use CFD models to simulate airborne concentrations of contaminants in an actual BSL-2 laboratory under different configurations. Results show that ventilation configuration, sampling location, and contaminant source location can significantly impact airborne concentrations and exposures. Depending on the source location and airflow patterns, the transient and time-integrated concentrations varied by several orders of magnitude. Contaminant plumes from sources located near a return vent (or exhaust like a fume hood or ventilated biosafety cabinet) are likely to be more contained than sources that are further from the exhaust. Having a direct flow between the source and the exhaust (through-flow condition) may reduce potential exposures to individuals outside the air flow path. Designing a BSL-2 room with ventilation and airflow patterns that maximize through-flow conditions to the return/exhaust vents and minimize dispersion and mixing throughout the room is, therefore, recommended. CFD simulations can also be used to assist in characterizing the impacts of supply and return vent locations, room layout, and source locations on spatial and temporal contaminant concentrations. In addition, proper placement of particle sensors can also be informed by CFD simulations to provide additional characterization and monitoring of potential exposures in BSL-2 facilities.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

NASA NTRS1992

Time and polarization dependent double scattering calculations of lidar returns from water clouds

We describe and present results of a double scattering lidar model which we use to calculate lidar returns from water clouds. The model is used in conjunction with the Phillips Laboratory's (Geophysics Directorate) low altitude Nd:YAG lidar system to determine microphysical properties of water clouds. The model determines the Stokes parameters of the backscattered lidar radiation, from media composed of spherical particles, as a function of time. The Stokes parameters of the radiation of the lidar return are determined, at each time, by considering all radiation which has traveled the same path length from transmitter to receiver while making two successive single scatters. Each single scatter is considered a Mie scatter. We have also developed a Mie scattering program for use with the double scattering model. Each single scatter takes into account the polarization of the incident and scattered radiation. Inputs to the double scattering mode include the receiver area and field of view, the receiver integration time, the extinction coefficient as a function of distance into the cloud, the particle size distribution (assumed independent of position), and the complex index of refraction of the spherical particles.

Garner, R. C.↗

NASA NTRS2017

Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design

A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.

Karr, David A.↗

NASA NTRS2023

Channel Measurements for Switching Strategies in Hybrid RF/Optical Communications

Free space optical (FSO) communication links increase data rate, reduce size and power, and increase security. These criteria are particularly important in space communication. Increasing mission complexity and crowding of lower frequency bands is driving the need for optical communications. This makes FSO communication technology extremely attractive, and there is significant ongoing work towards the development of FSO transceivers, ground stations, and relays. Notable projects include the Laser Communications Relay Demonstrator (LCRD), Integrated LCRD Low-Earth Orbit User Modem and Amplifier Terminal (ILLUMA-T), and CubeSat Laser Infrared Crosslink (CLICK) CubeSats. These technologies will eventually operate in unison with existing Radio Frequency (RF) systems, but there is little experimental investigation of such hybrid networks. This paper presents some experimental underpinnings of switching strategies for hybrid RF/FSO systems in various attenuation conditions. A 170 m optical path was constructed in an enclosed test chamber where atmospheric conditions can be tightly controlled. The performance of a 1550 nm infrared FSO link was evaluated in this chamber under varying conditions of turbulence and jitter. The system will eventually be used to investigate switching criteria between the FSO and RF channels. Optimizing the use of RF/FSO communication links will allow data rate, size, power, and security improvements. Therefore, this research will help to mature the network architecture and improve the performance of communication networks to be used for LEO, GEO, Lagrange, Lunar missions and beyond.

Space Networks↗

NASA NTRS2013

Estimated Probability of a Cervical Spine Injury During an ISS Mission

Introduction: The Integrated Medical Model (IMM) utilizes historical data, cohort data, and external simulations as input factors to provide estimates of crew health, resource utilization and mission outcomes. The Cervical Spine Injury Module (CSIM) is an external simulation designed to provide the IMM with parameter estimates for 1) a probability distribution function (PDF) of the incidence rate, 2) the mean incidence rate, and 3) the standard deviation associated with the mean resulting from injury/trauma of the neck. Methods: An injury mechanism based on an idealized low-velocity blunt impact to the superior posterior thorax of an ISS crewmember was used as the simulated mission environment. As a result of this impact, the cervical spine is inertially loaded from the mass of the head producing an extension-flexion motion deforming the soft tissues of the neck. A multibody biomechanical model was developed to estimate the kinematic and dynamic response of the head-neck system from a prescribed acceleration profile. Logistic regression was performed on a dataset containing AIS1 soft tissue neck injuries from rear-end automobile collisions with published Neck Injury Criterion values producing an injury transfer function (ITF). An injury event scenario (IES) was constructed such that crew 1 is moving through a primary or standard translation path transferring large volume equipment impacting stationary crew 2. The incidence rate for this IES was estimated from in-flight data and used to calculate the probability of occurrence. The uncertainty in the model input factors were estimated from representative datasets and expressed in terms of probability distributions. A Monte Carlo Method utilizing simple random sampling was employed to propagate both aleatory and epistemic uncertain factors. Scatterplots and partial correlation coefficients (PCC) were generated to determine input factor sensitivity. CSIM was developed in the SimMechanics/Simulink environment with a Monte Carlo wrapper (MATLAB) used to integrate the components of the module. Results: The probability of generating an AIS1 soft tissue neck injury from the extension/flexion motion induced by a low-velocity blunt impact to the superior posterior thorax was fitted with a lognormal PDF with mean 0.26409, standard deviation 0.11353, standard error of mean 0.00114, and 95% confidence interval [0.26186, 0.26631]. Combining the probability of an AIS1 injury with the probability of IES occurrence was fitted with a Johnson SI PDF with mean 0.02772, standard deviation 0.02012, standard error of mean 0.00020, and 95% confidence interval [0.02733, 0.02812]. The input factor sensitivity analysis in descending order was IES incidence rate, ITF regression coefficient 1, impactor initial velocity, ITF regression coefficient 2, and all others (equipment mass, crew 1 body mass, crew 2 body mass) insignificant. Verification and Validation (V&V): The IMM V&V, based upon NASA STD 7009, was implemented which included an assessment of the data sets used to build CSIM. The documentation maintained includes source code comments and a technical report. The software code and documentation is under Subversion configuration management. Kinematic validation was performed by comparing the biomechanical model output to established corridors.

Brooker, John E.↗

DOE OSTI2025

Unraveling Hydrogen Induced Geochemical Reaction Mechanisms through Coupled Geochemical Modeling and Machine Learning

Underground hydrogen storage (UHS) provides a promising large-scale, long-term energy storage solution. A reasonable recovery of stored hydrogen is critical for a successful storage scheme. However, in subsurface reservoirs hydrogen is subject to active geochemical reactions that might result in hydrogen loss. In this study, we implemented a geochemical modeling approach coupled with an unsupervised machine learning technique called non-negative matrix factorization (NMF) to unravel the complex brine-rock-H 2 geochemical processes responsible for hydrogen losses, with particular focus on sulfate reduction reactions. NMF is applied to modeled mineral evolution and fluid component profiles to retrieve profiles that can be interpreted to more easily assess competing processes. NMF decouples simulated competing equilibrium reactions. This facilitates separation of overlapping reaction profiles from redox processes, dissolution fronts, and secondary precipitation while considering the effects of simulation parameters such as salinity, temperature, and total H 2 pressure. NMF successfully discriminates these competing effects in nonlinear ways, allowing robust interpretation. In addition, NMF reveals subtle coupled mineral associations and reaction fronts that are invisible to conventional model analysis. This integrated approach strengthens the conceptual understanding of complex nonlinear hydrogen-brine-rock interactions and advances geochemical research on UHS systems to resolve complexities in modeled geochemical systems without the need for direct experiments or prior knowledge. Furthermore, this study highlights the efficacy of combining geochemical modeling with machine learning techniques to enhance the interpretability of the intricate geochemical simulation output through deciphering the overlapping reaction path that cannot be achieved only using conventional analysis of geochemical models alone.

08 HYDROGEN↗

DOE OSTI2026

A non-intrusive framework using acoustic signals and deep learning for boiling diagnostics in visual-limited environments

Accurate monitoring of boiling heat transfer is critical for safeguarding high-power systems operating in environments where conventional optical diagnostics are hindered by radiation fields or restricted visual accessibility. This study presents a non-intrusive framework that integrates hydroacoustic sensing with deep learning to infer near-wall boiling characteristics and enable predictive thermal assessment without visual access. In a prototypical subcooled flow-boiling facility representative of the Isotope Production Facility (IPF) at Los Alamos, hydrophones capture boiling-induced acoustic emissions that are transformed into background-removed Short-Time Fourier Transform (STFT) spectrograms. A convolutional neural network (CNN) then regresses heat flux, wall superheat, and key bubble parameters directly from these spectrograms. The CNN achieved predictive accuracy under nominal conditions and demonstrated robustness and generalization under acoustic noise for Signal-to-Noise Ratios (SNRs) down to approximately 0 dB. When integrated into an ANSYS CFX wall-boiling model, the acoustically inferred parameters reproduced boiling curve and critical heat flux (CHF) values consistent with image-based benchmarks. Furthermore, the model retained reliable performance under moderate variations in bulk temperature, flow rate, and hydrophone placement, confirming its generalizability across practical boundary conditions. These results demonstrate the feasibility of hydroacoustic-based deep learning as a viable path toward real-time, radiation-tolerant boiling diagnostics and predictive thermal safety assessment in inaccessible systems such as the IPF.

42 ENGINEERING↗

DOE OSTI2026

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Release of Evaluated 235 U(n,f) Average Prompt Fission Neutron Multiplicities Including the CGMF Model

This report documents an evaluation of the average prompt fission neutron multiplicity, $\overline{v}_p$, of 235 U from 200 keV to 15 MeV that is a potential release candidate for the upcoming U.S. nuclear data library, ENDF/B-VIII.1. This evaluation had to be re-done from "scratch", as the input to the $\overline{v}_p$ evaluation of the previous library, ENDF/B-VIII.0, was lost. That means that all available experimental data were re-analyzed and uncertainties were re-estimated. Another major difference to ENDF/B-VIII.0 is that this evaluation includes model information from the Hauser-Feshbach fission fragment decay code CGMF, while ENDF/B-VIII.0 is based purely on experimental data. CGMF links several fission quantities with each other; $\overline{v}_p$ is predicted by assumptions made on, e.g., pre-neutron emission yields as a function of mass, the total kinetic energy, or spin and parity of fission fragments. This allows to perform two types of validation for the new 235 U $\overline{v}_p$: On the one hand, one can employ evaluated CGMF parameters obtained from fitting to experimental 235 U $\overline{v}_p$ to predict yields as a function of mass, the average total kinetic energy, or the mean energy of the prompt fission neutron spectrum. These model-predicted values can then be compared to experimental and evaluated data. The model-predicted fission-observable values using evaluated parameters obtained here are reasonably close to experimental data indicating the evaluated 235 U(n,f) $\overline{v}_p$ are physical. On the other hand, one can validate 235 U $\overline{v}_p$ with respect to integral responses such as fast ICSBEP critical assemblies or LLNL pulsed spheres. LLNL pulsed-sphere neutron-leakage spectra are minimally impacted by the new 235 U $\overline{v}_p$ as these experimental data are shape data and the $\overline{v}_p$ would mostly lead to a change in normalization of the data as the spheres are relatively thin (0.7 and 1.5 mean-free path) and, thus, mostly depend on 235 U $\overline{v}_p$ from 12-15 MeV. The change in the predicted effective neutron multiplication factor, k eff , of selected ICSBEP critical assemblies, however, is large compared to values using ENDF/B-VIII.0 and experimental k eff : The average bias is 108 pcm across all studied k eff values versus 12 pcm for ENDF/B-VIII.0. A reasonable performance in simulating keff (mean bias of 14 pcm) can be retained by tweaking 235 U $\overline{v}_p$ from 3-5 MeV, and combining it with a recent 235 U PFNS evaluation that is also a ENDF/B-VIII.1 release candidate.

235U↗

NASA NTRS1984

A flight test evaluation of the pilot interface with a digital advanced avionics system

A flight study was conducted to study pilot workload and the pilot interface with high levels of avionics capability and automation. The study was done in the context of general aviation, single-pilot IFR operations and utilized an experimental, digital, integrated avionics system. Results indicate that such advanced systems can provide improved information to the pilot and increased functional capability. The results also indicate that additional research is needed to increase the knowledge base required to design the pilot interfaces with highly capable systems. A CRT-based moving map display format tested provided excellent navigational situational awareness but was inferior to an HSI for manual path tracking. The complexity of navigation data management, autopilot management, and maintaining awareness of system status contributed to pilot workload and errors. Suggested guidelines for the design of the pilot/avionics interface for advanced avionics systems are given.

Hinton, D. A.↗

NASA NTRS1984

IAC user manual

The User Manual for the Integrated Analysis Capability (IAC) Level 1 system is presented. The IAC system currently supports the thermal, structures, controls and system dynamics technologies, and its development is influenced by the requirements for design/analysis of large space systems. The system has many features which make it applicable to general problems in engineering, and to management of data and software. Information includes basic IAC operation, executive commands, modules, solution paths, data organization and storage, IAC utilities, and module implementation.

Vos, R. G.↗

NASA NTRS1994

Local dynamic subgrid-scale models in channel flow

The dynamic subgrid-scale (SGS) model has given good results in the large-eddy simulation (LES) of homogeneous isotropic or shear flow, and in the LES of channel flow, using averaging in two or three homogeneous directions (the DA model). In order to simulate flows in general, complex geometries (with few or no homogeneous directions), the dynamic SGS model needs to be applied at a local level in a numerically stable way. Channel flow, which is inhomogeneous and wall-bounded flow in only one direction, provides a good initial test for local SGS models. Tests of the dynamic localization model were performed previously in channel flow using a pseudospectral code and good results were obtained. Numerical instability due to persistently negative eddy viscosity was avoided by either constraining the eddy viscosity to be positive or by limiting the time that eddy viscosities could remain negative by co-evolving the SGS kinetic energy (the DLk model). The DLk model, however, was too expensive to run in the pseudospectral code due to a large near-wall term in the auxiliary SGS kinetic energy (k) equation. One objective was then to implement the DLk model in a second-order central finite difference channel code, in which the auxiliary k equation could be integrated implicitly in time at great reduction in cost, and to assess its performance in comparison with the plane-averaged dynamic model or with no model at all, and with direct numerical simulation (DNS) and/or experimental data. Other local dynamic SGS models have been proposed recently, e.g., constrained dynamic models with random backscatter, and with eddy viscosity terms that are averaged in time over material path lines rather than in space. Another objective was to incorporate and test these models in channel flow.

Cabot, William H.↗

NASA NTRS2006

Satellite-based Assessment of Global Warm Cloud Properties Associated with Aerosols, Atmospheric Stability, and Diurnal Cycle

This study examines variability in marine low cloud properties derived from semi-global observations by the Tropical Rainfall Measuring Mission (TRMM) satellite, as linked to the aerosol index (AI) and lower-tropospheric stability (LTS). AI is derived from the Moderate Resolution Imaging Spectroradiometer (Terra MODIS) sensor and the Goddard Chemistry Aerosol Radiation and Transportation (GOCART) model, and is used to represent column-integrated aerosol concentrations. LTS is derived from the NCEP/NCAR reanalysis, and represents the background thermodynamic environment in which the clouds form. Global statistics reveal that cloud droplet size tends to be smallest in polluted (high-AI) and strong inversion (high-LTS) environments. Statistical quantification shows that cloud droplet size is better correlated with AI than it is with LTS. Simultaneously, the cloud liquid water path (CLWP) tends to decrease as AI increases. This correlation does not support the hypothesis or assumption that constant or increased CLWP is associated with high aerosol concentrations. Global variability in corrected cloud albedo (CCA), the product of cloud optical depth and cloud fraction, is very well explained by LTS, while both AI and LTS are needed to explain local variability in CCA. Most of the local correlations between AI and cloud properties are similar to the results from the global statistics, while weak anomalous aerosol-cloud correlations appear locally in the regions where simultaneous high (low) AI and low (high) LTS compensate each other. Daytime diurnal cycles explain additional variability in cloud properties. CCA has the largest diurnal cycle in high-LTS regions. Cloud droplet size and CLWP have weak diurnal cycles that differ between clean and polluted environments. The combined results suggest that investigations of marine low cloud radiative forcing and its relationship to hypothesized aerosol indirect effects must consider the combined effects of aerosols, thermodynamics, and the diurnal cycle.

Matsui, Toshihisa↗

NASA NTRS2011

Monitoring Delamination of Thermal Barrier Coating During Interrupted High-Heat Flux Laser Testing Using Upconversion Luminescence Imaging

Upconversion luminescence imaging of thermal barrier coatings (TBCs) has been shown to successfully monitor TBC delamination progression during interrupted furnace cycling. However, furnace cycling does not adequately model engine conditions where TBC-coated components are subjected to significant heat fluxes that produce through-thickness temperature gradients that may alter both the rate and path of delamination progression. Therefore, new measurements are presented based on luminescence imaging of TBC-coated specimens subjected to interrupted high-heat-flux laser cycling exposures that much better simulate the thermal gradients present in engine conditions. The TBCs tested were deposited by electron-beam physical vapor deposition (EB-PVD) and were composed of 7wt% yttria-stabilized zirconia (7YSZ) with an integrated delamination sensing layer composed of 7YSZ co-doped with erbium and ytterbium (7YSZ:Er,Yb). The high-heat-flux exposures that produce the desired through-thickness thermal gradients were performed using a high power CO2 laser operating at a wavelength of 10.6 microns. Upconversion luminescence images revealed the debond progression produced by the cyclic high-heat-flux exposures and these results were compared to that observed for furnace cycling.

Eldridge, Jeffrey I.↗

NASA NTRS2023

Two Decades of Land Cover Change and Forest Fragmentation in Liberia: Consequences for the Contribution of Nature to People

The Guinean forests of West Africa have been identified as a global biodiversity hotspot due to its exceptional concentrations of endemic species and exceptional loss of habitats. The majority of what remains of the Guinean forests lies within Liberia, a country whose share of total wealth is nearly equally distributed into human and natural capital. The Liberian government seeks a more inclusive development agenda that forges a path for improved human capital while sustainably managing its natural capital wealth, which requires consistent data on land cover change and forest disturbance over time. To address this need, Landsat data were used to map and quantify land cover change and forest fragmentation in Liberia between 2000 and 2018. In addition, LiDAR data from the Global Ecosystem Dynamics Investigation (GEDI) mission were applied to assess the integrity of forest remnants. Between 2000 and 2018, only 1% of all forest cover classes (i.e., dense/primary, open/secondary and sparse/degraded) were converted into non-forest classes, with the most observed change being between these three forest classes. During the study period, 27% of the dense/primary forest class transitioned to either the open/secondary or sparse/degraded canopy classes through consistent fragmentation along the edges of the last large remaining blocks of dense/primary forest located in the north-west and south-east of Liberia and more than 14% of dense/primary forest areas identified in previous studies as “essential natural capital” for either biodiversity, forest carbon storage or provision of freshwater ecosystem services were degraded. The 2018 GEDI-based measurements show that the overall average height of dense/primary forest decreases by 24% and 48%, and canopy closure decreases by 33% and 59%, when transitioned to the open/secondary and sparse/degraded classes, respectively. The information derived from this analysis will be critical for informing the development of new policies and actions, leading to more sustainable forest management in Liberia.

Celio De Sousa↗

NASA NTRS1990

A parameterization for the shortwave transmissivity of stratiform water clouds based on empirical data and radiative transfer theory

Surface measurements of solar flux and total integrated liquid-water content, radiosonde data, and infrared satellite images are analyzed in conjunction with radiative transfer calculations to derive an empirical parameterization for the shortwave transmissivity of continental stratiform water clouds. The data were collected near Denver, Colorado, over a period of six years. A multiple reflection radiative transfer model is employed to estimate stratus cloud transmissivity in terms of the measurable liquid-water path (LWP). A nonlinear fit of estimated transmissivities to the corresponding observations of LWP yields close agreement with a previous, more complicated parameterization. The derived expression for cloud transmissivity is used to predict mean daily surface fluxes for 61 days during which periods of stratiform clouds were observed over the Denver area. A comparison between predicted and measured fluxes shows agreement to within + or - 4 percent, with best agreement for clouds of moderate optical thickness. Potential sources of error are identified with sensitivity studies.

Derr, V. E.↗

NASA NTRS1993

Geolocation applications of the Gonets LEO messaging satellites

Geostationary satellites carry a majority of the international telecommunications traffic not carried by transoceanic cable. However, because the radio path links to and from geostationary satellites total at least 70,000 km and because of inherent on-board spacecraft power limitations, earth stations used in conjunction with geostationary satellites are usually large and expensive. This limits their installation to areas with a well-developed industrial and economic infrastructure. This reality helps perpetuate a chicken egg dilemma for the developing countries and isolated regions. Economic integration with the developed world requires being 'networked'. But for many developing entities, even the initial price of entry exceeds their modest resources. Exclusion from the global information highways virtually assures retardation of economic growth for developing nations, remote and isolated areas. Very Small Aperture Terminal (VSAT) earth stations are often thought of as a solution for networking developing regions. But economic considerations often forecloses this option. If VSAT size and cost is to be minimized, powerful spot beams from the satellite need to be focused on relatively small regions. This is not often feasible because of the high cost of the satellite itself. To dedicate a high power spot beam to a small region is usually not economically feasible.

Vlasov, Vladimir N.↗

NASA NTRS1998

Wall effects observed in tissue-equivalent proportional counters from 1.05 GeV/nucleon iron-56 particles

Tissue-equivalent proportional counters (TEPCs) have been used to measure energy deposition in simulated volumes of tissue ranging in diameter from 0.1 to 10 microm. There has been some concern that the wall used to define the volume of interest could influence energy deposition within the sensitive volume because it has a density significantly greater than that of the cavity gas. These effects become important for high-velocity heavy ions. Measurements of energy deposition were made for 1 GeV/nucleon iron particles in a TEPC simulating a 1-microm-diameter sphere of tissue. The TEPC was nested within a particle spectrometer that provided identification and flight path of individual particles. Energy deposition was studied as a function of pathlength through the TEPC. Approximately 30% of the energy transfer along trajectories through the center of the detector escapes the sensitive volume. The response of the TEPC, for trajectories through the detector, is always larger than calculations for energy loss in a homogeneous medium. This enhancement is greatest for trajectories near the cavity/wall interface. An integration of the response indicates that charged-particle equilibrium is essentially achieved for a wall thickness of 2.54 mm. However, estimates of the linear energy transfer for the incident particles are influenced by these wall effects.

Non-NASA Center↗