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At least 883 records · Page 49

The role of topography in geodetic gravity field modelling

Masses associated with the topography, bathymetry, and its isostatic compensation are a dominant source of gravity field variations, especially at shorter wavelengths. On global scales the topographic/isostatic effects are also significant, except for the lowest harmonics. In practice, though, global effects need not be taken into account as such effects are included in the coefficients of the geopotential reference fields. On local scales, the short-wavelength gravity variations due to the topography may, in rugged terrain, be an order of magnitude larger than other effects. In such cases, explicit or implicit terrain reduction procedures are mandatory in order to obtain good prediction results. Such effects may be computed by space-domain integration or by fast Fourier transformation (FFT) methods. Numerical examples are given for areas of the Canadian Rockies. In principle, good knowledge of the topographic densities is required to produce the smoothest residual field. Densities may be determined from sample measurements or by gravimetric means, but both are somewhat troublesome methods in practice. The use of a standard density, e.g., 2.67 g/cu cm, may often yield satisfactory results and may be put within a consistent theoretical framework. The independence of density assumptions is the key point of the classical Molodensky approach to the geodetic boundary value problem. The Molodensky solutions take into account that land gravity field observations are done on a non-level surface. Molodensky's problem may be solved by integral expansions or more effective FFT methods, but the solution should not be intermixed with the use of terrain reductions. The methods are actually complimentary and may both be required in order to obtain the smoothest possible signal, least prone to aliasing and other effects coming from sparse data coverage, typical of rugged topography.

Forsberg, R.↗

Soil phosphorus drawdown by perennial bioenergy cropping systems in the Midwestern US

Abstract Without fertilization, harvest of perennial bioenergy cropping systems diminishes soil nutrient stocks, yet the time course of nutrient drawdown has not often been investigated. We analyzed phosphorus (P) inputs (fertilization and atmospheric deposition) and outputs (harvest and leaching losses) over 7 years in three representative biomass crops—switchgrass ( Panicum virgatum L.), miscanthus ( Miscanthus × giganteus ) and hybrid poplar trees ( Populus nigra × P. maximowiczii )—as well as in no‐till corn (maize; Zea mays L.) for comparison, all planted on former cropland in SW Michigan, USA. Only corn received P fertilizer. Corn (grain and stover), switchgrass, and miscanthus were harvested annually, while poplar was harvested after 6 years. Soil test P (STP; Bray‐1 method) was measured in the upper 25 cm of soil annually. Harvest P removal was calculated from tissue P concentration and harvest yield (or annual woody biomass accrual in poplar). Leaching was estimated as total dissolved P concentration in soil solutions sampled beneath the rooting depth (1.25 m), combined with hydrological modeling. Fertilization and harvest were by far the dominant P budget terms for corn, and harvest P removal dominated the P budgets in switchgrass, miscanthus, and poplar, while atmospheric deposition and leaching losses were comparatively insignificant. Because of significant P removal by harvest, the P balances of switchgrass, miscanthus, and poplar were negative and corresponded with decreasing STP, whereas P fertilization compensated for the harvest P removal in corn, resulting in a positive P balance. Results indicate that perennial crop harvest without P fertilization removed legacy P from soils, and continued harvest will soon draw P down to limiting levels, even in soils once heavily P‐fertilized. Widespread cultivation of bioenergy crops may, therefore, alter P balances in agricultural landscapes, eventually requiring P fertilization, which could be supplied by P recovery from harvested biomass.

09 BIOMASS FUELS↗

Microwave radiometer measurement of water vapor path delay: Data reduction techniques

Data reduction techniques are developed to compensate for water vapor path delay, a limiting error source in geodetic measurements made with very long baseline interferometry and in radio ranging to spacecraft. It is shown that water vapor path delay is proportional to a linear combination of saturation-corrected sky brightness temperatures, measured on and off the water vapor line. The effects of emission from liquid water droplets in clouds as well as most of the oxygen emission are removed by the off-line channel. Sky brightness temperatures are saturation-corrected or 'linearized' using estimates of effective sky temperatures made from surface temperature. Tipping curves are used to remove instrumental error. Coefficients are found by two methods: from a regression analysis of measured brightness temperatures versus radiosonde measured delay, and from a regression analysis of theoretical brightness temperatures versus radiosonde measured delay. In each case the coefficients are adjusted for differing climatic conditions by measurements of surface temperature, pressure, and relative humidity. Regression solutions are constrained to remove liquid water contributions and to give the correct slope for radiometer versus radiosonde path delay.

Claflin, E. S.↗

Thermally-Conductive Metallic Coatings and Applications for Heat Removal on In-Space Cryogenic Vehicles

For large in-space cryogenic upper stages, substantial axial heat removal from a forward skirt by vapor-based heat interception may not be achieved by simple attachment methods unless sufficient thermal conductance from the skirt to the cooling fluid can be achieved. Preferable methods would allow for the addition of the cooling system to existing structure with minimal impact on the structure. Otherwise, significant modification to the basic structural design andor novel and complex attachment mechanisms with high effective thermal conductance are likely to be required. The approach being pursued by evolvable Cryogenics (eCryo) is to increase the thermal performance of a relatively simple attachment system by applying metallic or other thermally conductive material coatings to the mating surface area of the fluid channel where it is attached the skirt wall. The expectation of candidate materials is that the dramatic increase in conductivity of pure metals at temperatures close to liquid hydrogen vapor temperature will compensate for the reduced actual contact area typical of mechanical joints. Basic contact conductance data at low temperatures for candidate interface materials is required to enable the test approach. A test rig was designed at NASA Glenn Research Center to provide thermal contact resistance testing between small sample coupons coated with conductive material via electron beam evaporation, a low-temperature option that will not affect physical properties of base materials. Average coating thicknesses were 10 k. The test fixture was designed to mount directly to a cryocooler cold head within a vacuum test chamber. The purpose of this test was to determine qualitative contact conductance between various test samples. Results from this effort will be implemented in a sub-scale vapor-based heat interception test, where the applicability for increased heat removal on large structural skirts will be considered.

small scale testing↗

Neural Learning Based Blind Source Separation for Detection of Material Defects in Pulsed Thermography Images

In this paper, we introduce a neural learning-based approach to blind source separation for detection of material flaws in pulsed thermography (PT) images. This approach can be used to detect internal defects (pores) in metallic Additively Manufactured (AM) materials. Such defects occur in high-strength alloys produced with direct laser sintering AM method for nuclear energy applications. Pulsed thermal imaging system utilizes a high intensity flash lamp to rapidly heat surface of sample, a high sensitivity infrared camera to capture data of surface temperature variations. The data cube obtained with PT (stack of surface temperature images at different times) can be analyzed with image processing algorithms to detect material defects. Compared with conventional nondestructive evaluation (NDE) methods, such as digital radiography and ultrasonic testing, the PT pulsed infrared thermal detection technique has advantages of one-sided non-contact measurements, fast processing of large sample areas captured in one image. Detection of small material defects requires finding features in thermal images, which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with the photothermic, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

Zhang, Xin↗

Cascade Error Projection: A Learning Algorithm for Hardware Implementation

In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.

Duong, Tuan A.↗

Radiometric Characterization of IKONOS Multispectral Imagery

A radiometric characterization of Space Imaging's IKONOS 4-m multispectral imagery has been performed by a NASA funded team from the John C. Stennis Space Center (SSC), the University of Arizona Remote Sensing Group (UARSG), and South Dakota State University (SDSU). Both intrinsic radiometry and the effects of Space Imaging processing on radiometry were investigated. Relative radiometry was examined with uniform Antarctic and Saharan sites. Absolute radiometric calibration was performed using reflectance-based vicarious calibration methods on several uniform sites imaged by IKONOS, coincident with ground-based surface and atmospheric measurements. Ground-based data and the IKONOS spectral response function served as input to radiative transfer codes to generate a Top-of-Atmosphere radiance estimate. Calibration coefficients derived from each vicarious calibration were combined to generate an IKONOS radiometric gain coefficient for each multispectral band assuming a linear response over the full dynamic range of the instrument. These calibration coefficients were made available to Space Imaging, which subsequently adopted them by updating its initial set of calibration coefficients. IKONOS imagery procured through the NASA Scientific Data Purchase program is processed with or without a Modulation Transfer Function Compensation kernel. The radiometric effects of this kernel on various scene types was also investigated. All imagery characterized was procured through the NASA Scientific Data Purchase program.

Pagnutti, Mary↗

An independent analysis of bias sources and variability in wind plant pre-construction energy yield estimation methods

The wind resource assessment community has long had the goal of reducing the bias between wind plant pre-construction energy yield assessment (EYA) and the observed annual energy production (AEP). This comparison is typically made between the 50% probability of exceedance (P50) value of the EYA and the long-term corrected operational AEP (hereafter OA P50), and is known as the P50 bias. The industry has critically lacked an independent analysis of bias reduction investigated across multiple consultants to identify the greatest sources of uncertainty and variance in the EYA process and the best opportunities for uncertainty reduction. The present study addresses this gap by benchmarking consultant methodologies against each other and against operational data at a scale not seen before in industry collaborations. We consider data from 10 wind plants and evaluate discrepancies between eight consultancies in the steps taken from estimates of gross to net energy. Consultants tend to overestimate the gross energy produced at the turbines and then compensate by further overestimating downstream losses, leading to a mean P50 bias near zero, still with significant variability among the individual wind plants. Within our data sample, we find that consultant estimates of all loss categories, except environmental losses, tend to reduce the project-to-project variability of the P50 bias. The disagreement between consultants, however, remains flat throughout the addition of losses. Finally, we find that differences in consultants’ estimates of project performance can lead to differences up to $10/MWh in the levelized cost of energy for a wind plant.

Todd, Austin C.↗

Bridging microscopy with molecular dynamics and quantum simulations: an atomAI based pipeline

Recent advances in (scanning) transmission electron microscopy have enabled a routine generation of large volumes of high-veracity structural data on 2D and 3D materials, naturally offering the challenge of using these as starting inputs for atomistic simulations. In this fashion, the theory will address experimentally emerging structures, as opposed to the full range of theoretically possible atomic configurations. However, this challenge is highly nontrivial due to the extreme disparity between intrinsic timescales accessible to modern simulations and microscopy, as well as latencies of microscopy and simulations per se. Addressing this issue requires as a first step bridging the instrumental data flow and physics-based simulation environment, to enable the selection of regions of interest and exploring them using physical simulations. Here we report the development of the machine learning workflow that directly bridges the instrument data stream into Python-based molecular dynamics and density functional theory environments using pre-trained neural networks to convert imaging data to physical descriptors. Additionally, the pathways to ensure structural stability and compensate for the observational biases universally present in the data are identified in the workflow. This approach is used for a graphene system to reconstruct optimized geometry and simulate temperature-dependent dynamics including adsorption of Cr as an ad-atom and graphene healing effects. However, it is universal and can be used for other material systems.

36 MATERIALS SCIENCE↗

Reliability and performance experience with flat-plate photovoltaic modules

Statistical models developed to define the most likely sources of photovoltaic (PV) array failures and the optimum method of allowing for the defects in order to achieve a 20 yr lifetime with acceptable performance degradation are summarized. Significant parameters were the cost of energy, annual power output, initial cost, replacement cost, rate of module replacement, the discount rate, and the plant lifetime. Acceptable degradation allocations were calculated to be 0.0001 cell failures/yr, 0.005 module failures/yr, 0.05 power loss/yr, a 0.01 rate of power loss/yr, and a 25 yr module wear-out length. Circuit redundancy techniques were determined to offset cell failures using fault tolerant designs such as series/parallel and bypass diode arrangements. Screening processes have been devised to eliminate cells that will crack in operation, and multiple electrical contacts at each cell compensate for the cells which escape the screening test and then crack when installed. The 20 yr array lifetime is expected to be achieved in the near-term.

Ross, R. G., Jr.↗

Correlative analysis of CsPbBr2Hal (Hal = Cl, Br, I) meltcrystallization paramete

Abstract — Metal halide perovskites (MHPs) are an exciting research topic as they have the potential to make solar cells that are both more efficient than current siliconbased designs and have a wider range of applications. In this work the crystallization of CsPbBr2Hal (Hal = Cl, Br, I) halide perovskite melts were studied by the differential thermal analysis method. It was established that the crystallization of CsPbBr2Hal (Hal = Cl, Br, I) melts can be “hot” (i.e., at temperatures above the point of the alloy’s start-melting temperature) or with supercooling. The replacement of the bromine atom with another halogen atom leads to a shift of the dwell temperature range, at which “hot” crystallization takes place, from 830-846 K for CsPbBr3 to 807-832 K for CsPbBr2Cl and 741-768 K for CsPbBr2I. The activation energy of “hot” crystallization decreases in the same order. A linear dependence between the pre-exponential factor (ln(𝑽𝑽𝒄𝒄𝒄𝒄𝒄𝒄𝒔𝒔𝒕𝒕 𝟎𝟎 )) and the activation energy (Ea) of the crystallization process is revealed from the experimental data, proving the compensation effect.

Kopach, O.↗

A method for generating quantitative vapor-phase infrared spectra of solids: results for phenol, camphor, menthol, syringol, dicyclopentadiene and naphthalene

Here, a method is presented to generate quantitative vapor-phase infrared spectra from substances that naturally occur as solids with moderate volatility. The solid is gravimetrically dissolved into a solvent that has few infrared spectral features, typically CS 2 and CCl 4 separately. The solution is flowed at a constant rate from a linearly pumped syringe into a metered stream of nitrogen carrier gas regulated by a mass flow controller. The analyte/solvent mix is flash vaporized by volatilizing the solution across a heated stainless-steel surface as it emanates from the syringe tip. The N 2 gas-solution mixture is flowed into a long-path White cell thermostatted at a desired temperature, the long optical path compensating for the modest analyte mixing ratio. A composite spectrum is generated from typically ten or more 760-Torr pressure-broadened spectra over the 600 to 6500 cm -1 spectral range at 0.1 cm -1 spectral resolution. The solid analytes reported here using this novel technique include dicyclopentadiene, menthol, syringol, phenol, camphor, and naphthalene.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Life-cycle costing assessment of back contact doping and encapsulation alternatives for increasing the life expectancy of CdTe PV modules (Final Report)

Contribution of Research to the State-of-Knowledge This research produced comparative sustainability evaluations of back contact doping and encapsulation alternatives considered by First Solar for decreasing degradation and increasing the life of the cadmium telluride (CdTe) photovoltaic (PV) modules. Technical Effectiveness and Economic Feasibility of Methods Investigated A holistic life-cycle-assessment of the alternatives considered for longer module operational lives, showed that they add between 0.2% and 2% to environmental impact indicators at the cradle-to-gate module level, but at the cradle-to-grave system level, alternative materials offer only benefits (i.e., environmental impact indicator decreases) to the public and the environment. Parallel experimental studies at First Solar showed that the use of the considered alternative materials did not impact the effectiveness of the current module recycling separations and material recovery processes. Furthermore, the increment on the module manufacturing cost due to using alternative materials was estimated to be negligible (i.e., >1%) and longer module lives more than compensate cost increases. Specifically, increase of the current warranted module life of 30 years to 50 years, would decrease the levelized cost of electricity (LCOE) from $40/MWh to $24/MWh for utility-scale installations in the US-SW, the economic feasibility of the considered alternatives is assured. Benefit to the Public With decreasing degradation from the current ~0.3%/year of Series 6 modules to less than 0.2%/year, the public will be benefited by longer photovoltaic operational lives, and therefore. In addition, the requirement for end-of-life management is shifted from 30 years to 40 or 50 years, with profound benefits to the public and the environment.

14 SOLAR ENERGY↗

Development of a Field-Deployable Microphone Phased Array for Airframe Noise Flyover Measurements

This technical memorandum describes in detail the construction and use of a large channel-count, field-deployable microphone phased array designed for airframe noise flyover measurements for a range of aircraft types and scales. The array incorporated 185 hardened, weather-resistant sensors suitable for outdoor use. A custom 4-mA current loop receiver circuit with temperature compensation was developed to power the sensors over extended cable lengths with minimal loss of signal-to-noise. Extensive calibrations and performance testing of the sensors were conducted to verify the design specifications. A compact data system combining sensor power, signal conditioning, and digitization was assembled for use with the array. Complementing the data system was a robust analysis system capable of near real-time presentation of beamformed and deconvolved contour plots and integrated spectra obtained from data acquired during flyover passes of the array. Additional instrumentation systems needed to process the array data were also developed, including a commercial 10-meter weather station comprised of a sonic anemometer, aspirated temperature/humidity probe and pressure sensor. Unique methods for assessing the health of the array in-situ were developed and demonstrated. A detailed mock-up of the instrumentation suite (phased array, weather station, and data processor) was performed in the NASA Langley Acoustic Development Laboratory in 2014 to vet the system performance. Issues with the sensors and electronics were identified during the mock-up and subsequently corrected. The array was then deployed for preliminary field testing at Fort A.P. Hill in Virginia in 2015 followed by the array being utilized in three separate full-scale airframe noise test campaigns at Edwards Air Force Base in California from 2016 to 2018 where the system was used to characterize the noise generated by both baseline and treated flaps and main landing gear on a commercial transport-sized vehicle.

Phased Array↗

Low Level Calibration of Liquid Scintillation Counting

Liquid Scintillation Counting (LSC) is an analytical laboratory method that quantifies the concentrations of alpha and beta emitting isotopes. The LSC method can be utilized for the detection of tritium, both environmentally and at nuclear facilities. Most LSC samples are aqueous-based and prepared as a radioactive sample dissolved or suspended in a high efficiency scintillation cocktail that converts radioactive energy into light pulses. When placed in counting vials, the liquid scintillation cocktail allows for optical coupling in which energy is released from the samples radioactive decay, and transferred to the scintillator. That energy is then absorbed to produce excited electrons that fall back to their ground-state and emit a pulse of light that is detected by the liquid scintillation analyzers photomultiplier tubes. Quench is a signal attenuation due to physical, chemical, or color interferences. To compensate for quench, quench standards of a known concentration are implemented at increasing increments of quench per vial to create a quench curve. Quench standards can be purchased pre-made or customized from the manufacturer, however, there are several issues that arise from purchasing the pre-made quench standards. The main issues with ordering pre-made quench standards is that they use higher count values, between 30,000 and 250,000 disintegrations per minute (dpm) of tritium per vial and only come in glass vials. Using higher counting standards in glass vials makes it hard to see lower concentrations in plastic vials. Additionally, when using higher energy standards the accuracy of the calibration readings tend to be lower. On the other hand, making a set of quench standards in-house allows for the customization of the dpm concentration to roughly 1,500-3,000 and preparation in plastic vials. This allows for lower activity readings that results in closer precision of the samples' true concentration. Technical Objectives: Create a quench curve and calibrate the LSA for tritium. Verify the calibration of the quench curve prior to cross sample runs. Check calibration against Quality Control (QC) reference value. Conclusion: a tritium quench curve calibration was performed using a scintillation cocktail with ultima gold (AB and AB/F), acetone (only with AB), and water (only with AB/F). By performing the tritium quench curve calibration, the counting efficiency was correlated to various levels of quench. Calibration checks with quality control standards were also performed to verify that the calibration was correct. The observed results provided acceptable values that matched the quality control standard reference values with an acceptable uncertainty. The next step will be fine tuning and cross comparison checks with legacy instrumentation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Compensated Contacts for Three-Terminal Transistor Solar Cells

The heterojunction bipolar transistor solar cell (HBTSC) is an alternative to conventional double-junction solar cells that combines the advantages of three-terminal architectures with a compact design. A critical part of the HBTSC fabrication is the implementation of the middle contact, the one associated to the base layer in the transistor structure, because this layer can be damaged by the diffusion of metallic species during contact annealing. As a solution we propose to implement a "compensated contact", that is, to leave a thin (< 200 nm) portion of emitter or collector between the base layer and the contact metals and compensate its doping during contact annealing. Using an Au/Zn/Au metal structure to compensate a 150 nm thick portion of the collector, we obtain a specific contact resistance ~8 10-4 ..omega.. cm2. This value is fairly invariant for annealing temperatures between 400 and 460 degrees C and annealing times between 2 and 5 minutes, and it does not improve by adding Pd to the metallic stack. Optimizing the compensated contact technology opens the path to the realization of III-V-material-based HBTSCs with open-circuit voltages and fill factors comparable to those of conventional multijunction architectures.

contact resistance↗

Response of deep and shallow tropical maritime cumuli to large-scale processes

The bulk diagnostic method of Yanai et al. (1973) and a simplified version of the spectral diagnostic method of Nitta (1975) are used for a more quantitative evaluation of the response of various types of cumuliform clouds to large-scale processes, using the same data set in the Marshall Islands area for a 100-day period in 1956. The dependence of the cloud mass flux distribution on radiative cooling, large-scale vertical motion, and evaporation from the sea is examined. It is shown that typical radiative cooling rates in the tropics tend to produce a bimodal distribution of mass spectrum exhibiting deep and shallow clouds. The bimodal distribution is further enhanced when the large-scale vertical motion is upward, and a nearly unimodal distribution of shallow clouds prevails when the relative cooling is compensated by the heating due to the large-scale subsidence. Both deep and shallow clouds are modulated by large-scale disturbances. The primary role of surface evaporation is to maintain the moisture flux at the cloud base.

Yanai, M.↗

Ionizing Radiation Environment on the International Space Station: Performance vs. Expectations for Avionics and Material

The role of structural shielding mass in the design, verification, and in-flight performance of International Space Station (ISS), in both the natural and induced orbital ionizing radiation (IR) environments, is reported. Detailed consideration of the effects of both the natural and induced ionizing radiation environment during ISS design, development, and flight operations has produced a safe, efficient manned space platform that is largely immune to deleterious effects of the LEO ionizing radiation environment. The assumption of a small shielding mass for purposes of design and verification has been shown to be a valid worst-case approximation approach to design for reliability, though predicted dependences of single event effect (SEE) effects on latitude, longitude, SEP events, and spacecraft structural shielding mass are not observed. The Figure of Merit (FOM) method over predicts the rate for median shielding masses of about 10g/cm(exp 2) by only a factor of 3, while the Scott Effective Flux Approach (SEFA) method overestimated by about one order of magnitude as expected. The Integral Rectangular Parallelepiped (IRPP), SEFA, and FOM methods for estimating on-orbit (Single Event Upsets) SEU rates all utilize some version of the CREME-96 treatment of energetic particle interaction with structural shielding, which has been shown to underestimate the production of secondary particles in heavily shielded manned spacecraft. The need for more work directed to development of a practical understanding of secondary particle production in massive structural shielding for SEE design and verification is indicated. In contrast, total dose estimates using CAD based shielding mass distributions functions and the Shieldose Code provided a reasonable accurate estimate of accumulated dose in Grays internal to the ISS pressurized elements, albeit as a result of using worst-on-worst case assumptions (500 km altitude x 2) that compensate for ignoring both GCR and secondary particle production in massive structural shielding.

Koontz, Steven L.↗