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

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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Low vibration high numerical aperture automated variable temperature Raman microscope

Raman micro-spectroscopy is well suited for studying a variety of properties and has been applied to wide- ranging areas. Combined with tuneable temperature, Raman spectra can offer even more insights into the properties of materials. However, previous designs of variable temperature Raman microscopes have made it extremely challenging to measure samples with low signal levels due to thermal and positional instability as well as low collection efficiencies. Thus, contemporary Raman microscope has found limited applicability to probing the subtle physics involved in phase transitions and hysteresis. This paper describes a new design of a closed-cycle, Raman microscope with full polarization rotation. High collection efficiency, thermal and mechanical stability are ensured by both deliberate optical, cryogenic, and mechanical design. Measurements on two samples, Bi 2 Se 3 and V 2 O 3 , which are known as challenging due to low thermal conductivities, low signal levels and/or hysteretic effects, are measured with previously undemonstrated temperature resolution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

On the turbulent flow in piston engines: Coupling of statistical theory quantities and instantaneous turbulence

Planar particle image velocimetry (PIV) and tomographic PIV (TPIV) measurements are utilized to analyze turbulent statistical theory quantities and the instantaneous turbulence within a single-cylinder optical engine. Measurements are performed during the intake and mid-compression stroke at 800 and 1500 RPM. TPIV facilitates the evaluation of spatially resolved Reynolds stress tensor (RST) distributions, anisotropic Reynolds stress invariants, and instantaneous turbulent vortical structures. The RST analysis describes distributions of individual velocity fluctuation components that arise from unsteady turbulent flow behavior as well as cycle-to-cycle variability (CCV). A conditional analysis, for which instantaneous PIV images are sampled by their tumble center location, reveals that CCV and turbulence have similar contributions to RST distributions at the mean tumble center, but turbulence is dominant in regions peripheral to the tumble center. Analysis of the anisotropic Reynolds stress invariants reveals the spatial distribution of axisymmetric expansion, axisymmetric contraction, and 3D isotropy within the cylinder. Findings indicate that the mid-compression flow exhibits a higher tendency toward 3D isotropy than the intake flow. A novel post-processing algorithm is utilized to classify the geometry of instantaneous turbulent vortical structures and evaluate their frequency of occurrence within the cylinder. Findings are coupled with statistical theory quantities to provide a comprehensive understanding of the distribution of turbulent velocity components, the distribution of anisotropic states of turbulence, and compare the turbulent vortical flow distribution that is theoretically expected to what is experimentally observed. The analyses reveal requisites of important turbulent flow quantities and discern their sensitivity to the local flow topography and engine operation.

42 ENGINEERING↗
DOE OSTI2025

Comparing three generations of D-Wave quantum annealers for minor embedded combinatorial optimization problems

Abstract Quantum annealing (QA) is a novel type of analog computation that aims to use quantum mechanical fluctuations to search for optimal solutions of Ising problems. QA in the transverse Ising model, implemented on D-Wave quantum processing units, are available as cloud computing resources. In this study we report concise benchmarks across three generations of D-Wave quantum annealers, consisting of four different devices, for the NP-hard discrete combinatorial optimization problems unweighted maximum clique and unweighted maximum cut on random graphs. The Ising, or equivalently quadratic unconstrained binary optimization, formulation of these problems do not require auxiliary variables for order reduction, and their overall structure and weights are not highly variable, which makes these problems simple test cases to understand the sampling capability of current D-Wave quantum annealers. All-to-all minor embeddings of size 52, with relatively uniform chain lengths, are used for a direct comparison across the Chimera, Pegasus, and Zephyr device topologies. A grid-search over annealing times and the minor embedding chain strengths is performed in order to determine the level of reasonable performance for each device and problem type. Experiment metrics that are reported are approximation ratios for non-broken chain samples, chain break proportions, and time-to-solution for the maximum clique problem instances. How fairly the quantum annealers sample optimal maximum cliques, for instances which contain multiple maximum cliques, is quantified using entropy of the measured ground state distributions. The newest generation of quantum annealing hardware, which has a Zephyr hardware connectivity, performed the best overall with respect to approximation ratios and chain break frequencies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Hopping crossover and high-temperature superspin glass behavior in Ni films deposited on MoS 2

Realizing the potential of MoS 2 and other two-dimensional semiconductors in spintronic devices requires a fundamental understanding of their interaction with ferromagnetic metals. We have investigated the transport and magnetic properties of thin Ni films grown on single-crystal MoS 2 substrates. The Ni is found to have a granular morphology with an average grain size of approximately 2 nm. Like previously investigated granular Ni/insulator composites below the percolation threshold, transport is found to proceed via hopping. However, our Ni/MoS 2 sample exhibits a dual crossover: activated hopping to 𝑇−1/2 variable-range hopping at a higher temperature and then a transition to power-law behavior at a lower temperature. The magnetoresistance was used as a novel probe for uncovering superspin-glass-like behavior above room temperature in the Ni/MoS 2 nanostructure, which also exhibits a collective ferromagnetic state at very low temperatures, reminiscent of superferromagnetism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Poster - 14: Batch Effect Reduction in in-vitro Raman Microscopic Radiosensitivity Study Using Ovarian Cancer Cells

Purpose: To improve classification by reducing batch effect in samples from the ovarian carcinoma cell lines A2780s (parental wild type) and A2780cp (cisplatin cross-radio-resistant), before, right after, and 24 hours after irradiation to 10Gy. Methods: Spectra were acquired with a home built confocal Raman microscope in 3 distinct runs of six samples: unirradiated s&cp (control pair), then 0h and 24h after irradiation. The Raman spectra were noise reduced, then background subtracted with SMIRF algorithm. ∼35 cell spectra were collected from each sample in 1024 channels from 700cm-1 to 1618cm-1. The spectra were analyzed by regularized multiclass LDA. For feature reduction the spectra were grouped into 3 overlapping group pairs: s-cp, 0Gy–10Gy0h and 0Gy10–Gy24h. The three features, the three differences of the mean spectra were mapped to the analysis sub-space by the inverse regularized covariance matrix. The batch effect noticeably confounded the dose and time effect. Results: To remove the batch effect, the 2+2=4D subspace extended by the covariance matrix of the means of the 0Gy control groups was subtracted from the spectra of each sample. Repeating the analysis on the spectra with the control group variability removed, the batch effect was dramatically reduced in the dose and time directions enabling sharp linear discrimination. The cell type classification also improved. Conclusions: We identified a efficient batch effect removal technique crucial to the applicability of Raman microscopy to radiosensitivity studies both on cell cultures and potential clinical diagnostic applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Large Circular Plasmids from Groundwater Plasmidomes Span Multiple Incompatibility Groups and Are Enriched in Multimetal Resistance Genes

ABSTRACT Naturally occurring plasmids constitute a major category of mobile genetic elements responsible for harboring and transferring genes important in survival and fitness. A targeted evaluation of plasmidomes can reveal unique adaptations required by microbial communities. We developed a model system to optimize plasmid DNA isolation procedures targeted to groundwater samples which are typically characterized by low cell density (and likely variations in the plasmid size and copy numbers). The optimized method resulted in successful identification of several hundred circular plasmids, including some large plasmids (11 plasmids more than 50 kb in size, with the largest being 1.7 Mb in size). Several interesting observations were made from the analysis of plasmid DNA isolated in this study. The plasmid pool (plasmidome) was more conserved than the corresponding microbiome distribution (16S rRNA based). The circular plasmids were diverse as represented by the presence of seven plasmid incompatibility groups. The genes carried on these groundwater plasmids were highly enriched in metal resistance. Results from this study confirmed that traits such as metal, antibiotic, and phage resistance along with toxin-antitoxin systems are encoded on abundant circular plasmids, all of which could confer novel and advantageous traits to their hosts. This study confirms the ecological role of the plasmidome in maintaining the latent capacity of a microbiome, enabling rapid adaptation to environmental stresses. IMPORTANCE Plasmidomes have been typically studied in environments abundant in bacteria, and this is the first study to explore plasmids from an environment characterized by low cell density. We specifically target groundwater, a significant source of water for human/agriculture use. We used samples from a well-studied site and identified hundreds of circular plasmids, including one of the largest sizes reported in plasmidome studies. The striking similarity of the plasmid-borne ORFs in terms of taxonomical and functional classifications across several samples suggests a conserved plasmid pool, in contrast to the observed variability in the 16S rRNA-based microbiome distribution. Additionally, the stress response to environmental factors has stronger conservation via plasmid-borne genes as marked by abundance of metal resistance genes. Last, identification of novel and diverse plasmids enriches the existing plasmid database(s) and serves as a paradigm to increase the repertoire of biological parts that are available for modifying novel environmental strains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Leveraging Intrinsic Principal Directions for Multifidelity Uncertainty Quantification

In this work we propose an approach for accelerating Uncertainty Quantification (UQ) analysis in the context of Multifidelity applications. In the presence of complex multiphysics applications, which often require a prohibitive computational cost for each evaluation, multifidelity UQ techniques try to accelerate the convergence of statistics by leveraging the in- formation collected from a larger number of a lower fidelity model realizations. However, at the-state-of-the-art, the performance of virtually all the multifidelity UQ techniques is related to the correlation between the high and low-fidelity models. In this work we proposed to design a multifidelity UQ framework based on the identification of independent important directions for each model. The main idea is that if the responses of each model can be represented in a common space, this latter can be shared to enhance the correlation when the samples are drawn with respect to it instead of the original variables. There are also two main additional advantages that follow from this approach. First, the models might be correlated even if their original parametrizations are chosen independently. Second, if the shared space between models has a lower dimensionality than the original spaces, the UQ analysis might benefit from a dimension reduction standpoint. In this work we designed this general framework and we also tested it on several test problems ranging from analytical functions for verification purpose, up to more challenging application problems as an aero-thermo-structural analysis and a scramjet flow analysis.

42 ENGINEERING↗
DOE OSTI2025

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing↗
DOE OSTI2023

Page curves and typical entanglement in linear optics

Bosonic Gaussian states are a special class of quantum states in an infinite dimensional Hilbert space that are relevant to universal continuous-variable quantum computation as well as to near-term quantum sampling tasks such as Gaussian Boson Sampling. In this work, we study entanglement within a set of squeezed modes that have been evolved by a random linear optical unitary. We first derive formulas that are asymptotically exact in the number of modes for the Rényi-2 Page curve (the average Rényi-2 entropy of a subsystem of a pure bosonic Gaussian state) and the corresponding Page correction (the average information of the subsystem) in certain squeezing regimes. We then prove various results on the typicality of entanglement as measured by the Rényi-2 entropy by studying its variance. Using the aforementioned results for the Rényi-2 entropy, we upper and lower bound the von Neumann entropy Page curve and prove certain regimes of entanglement typicality as measured by the von Neumann entropy. Our main proofs make use of a symmetry property obeyed by the average and the variance of the entropy that dramatically simplifies the averaging over unitaries. In this light, we propose future research directions where this symmetry might also be exploited. We conclude by discussing potential applications of our results and their generalizations to Gaussian Boson Sampling and to illuminating the relationship between entanglement and computational complexity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Enhancing Model Predictability for a Scramjet Using Probabilistic Learning on Manifolds

In this study, the computational burden of a large-eddy simulation for reactive flows is exacerbated in the presence of uncertainty in flow conditions or kinetic variables. A comprehensive statistical analysis, with a sufficiently large number of samples, remains elusive. Statistical learning is an approach that allows for extracting more information using fewer samples. Such procedures, if successful, will greatly enhance the predictability of models in the sense of improving exploration and characterization of uncertainty due to model error and input dependencies, all while being constrained by the size of the associated statistical samples. In this paper, it is shown how a recently developed procedure for probabilistic learning on manifolds can serve to improve the predictability in a probabilistic framework of a scramjet simulation. The estimates of the probability density functions of the quantities of interest are improved together with estimates of the statistics of their maxima. Lastly, it is also demonstrated how the improved statistical model adds critical insight to the performance of the model.

42 ENGINEERING↗
DOE OSTI2024

Circulating levels of micronutrients and risk of osteomyelitis: a Mendelian randomization study

Background Few observational studies have investigated the effect of micronutrients on osteomyelitis, and these findings are limited by confounding and conflicting results. Therefore, we conducted Mendelian randomization (MR) analyses to evaluate the association between blood levels of eight micronutrients (copper, selenium, zinc, vitamin B12, vitamin C, and vitamin D, vitamin B6, vitamin E) and the risk of osteomyelitis. Methods We performed the two-sample and multivariable Mendelian randomization (MVMR) to investigate causation, where instrument variables for the predictor (micronutrients) were derived from the summary data of micronutrients from independent cohorts of European ancestry. The outcome instrumental variables were used from the summary data of European-ancestry individuals ( n = 486,484). The threshold of statistical significance was set at p < 0.00625. Results We found a significant causal association that elevated zinc heightens the risk of developing osteomyelitis in European ancestry individuals OR = 1.23 [95% confidence interval (CI) [1.07, 1.43]; p = 4.26E-03]. Similarly, vitamin B6 showed a similar significant causal effect on osteomyelitis as a risk factor OR = 2.78 (95% CI [1.34, 5.76]; p = 6.04E-03; in the secondary analysis). Post-hoc analysis suggested this result (vitamin B6). However, the multivariable Mendelian randomization (MVMR) provides evidence against the causal association between zinc and osteomyelitis OR = 0.98(95% CI [−0.11, 0.07]; p = 7.20E-1). After searching in PhenoScanner, no SNP with confounding factors was found in the analysis of vitamin B6. There was no evidence of a reverse causal impact of osteomyelitis on zinc and vitamin B6. Conclusion This study supported a strong causal association between vitamin B6 and osteomyelitis while reporting a dubious causal association between zinc and osteomyelitis.

Zhang, Xu↗
NASA NTRS1972

Airborne measurements of air pollution chemistry and transport. 1: Initial survey of major air basins in California

An instrumented aircraft has been used to study photochemical air pollution in the State of California. Simultaneous measurements of the most important chemical constituents (ozone, total oxidant, hydrocarbons, and nitrogen oxides, as well as several meteorological variables) were made. State-of-the-art measurement techniques and sampling procedures are discussed. Data from flights over the South Coast Air Basin, the San Francisco Bay Area, the San Joaquin Valley, the Santa Clara and Salinas Valleys, and the Pacific Ocean within 200 miles of the California coast are presented. Pollutants were found to be concentrated in distant layers up to at least 18,000 feet. In many of these layers, the pollutant concentrations were much higher than at ground level. These findings bring into serious question the validity of the present practice of depending solely on data from ground-based monitoring stations for predictive models.

Gloria, H. R.↗
NASA NTRS1974

Liquid rocket combustion computer model with distributed energy release. DER computer program documentation and user's guide, volume 1

A computer program for analyzing rocket engine performance was developed. The program is concerned with the formation, distribution, flow, and combustion of liquid sprays and combustion product gases in conventional rocket combustion chambers. The capabilities of the program to determine the combustion characteristics of the rocket engine are described. Sample data code sheets show the correct sequence and formats for variable values and include notes concerning options to bypass the input of certain data. A seperate list defines the variables and indicates their required dimensions.

Combs, L. P.↗
NASA NTRS1981

Effects of aircraft noise on the equilibrium of airport residents: Supplementary analyses to the study carried out around Orly

The effects of aircraft noise on humans living near airports were studied. Two main questions were considered: do residents give evidence of psychological or physiological disturbances in unusually intense noise sectors; and do personality or health factors account for the high interindividual variability of annoyance? The methodology used and results obtained are presented. Samples of the survey questionnaires are included.

Francois, J.↗
NASA NTRS1984

Estimating the Lifetimes of Nickel/Cadmium Cells

Equation based on model of flaw growth. Model assumes cell fails by growth of preexisting flaws. Flaws described by three important quantities: total number of flaws, distribution of flaw sizes and rate of flaw growth. When flaw reaches critical size failure occurs. Flaw concept, in addition to providing ready explanation for reduced lifetime, predicts two important charateristics: statistical variability of lifetime data and dependence of lifetime on volume of sample.

Fedors, R. F.↗
NASA NTRS1987

Electrodynamics of the middle atmosphere: Superpressure balloon program

In this experiment a comprehensive set of electrical parameters were measured during eight long duration flights in the southern hemisphere stratosphere. These flight resulted in the largest data set ever collected from the stratosphere. The stratosphere has never been electrodynamically sampled in the systematic manner before. New discoveries include short term variability in the planetary scale electric current system, the unexpected observation of stratospheric conductivity variations over thunderstorms and the observation of direct stratospheric conductivity variations following a relatively small solar flare. Major statistical studies were conducted of the large scale current systems, the stratospheric conductivity and the neutral gravity waves (from pressure and temperature data) using the entire data set.

Holzworth, Robert H.↗
NASA NTRS1989

Tensile film clamps and mounting block for the rheovibron and autovibron viscoelastometer

A set of film clamps and a mounting block for use in the determination of tensile modulus and damping properties of films in a manually operated or automated Rheovibron is diagrammed. These clamps and mounting block provide uniformity of sample gripping and alignment in the instrument. Operator dependence and data variability are greatly reduced.

Stoakley, Diane M.↗
NASA NTRS1993

Experimental effects of wing location on wing-body pressures at supersonic speeds

An experimental study was performed at supersonic speeds to measure wing and body spanwise pressure distributions on an axisymmetric-body delta wing model on which the wing vertical location on the body was systematically varied from low- to high-mounted positions. In addition, for two of these positions both horizontal and radial wing angular orientations relative to the body were tested, and roll angle effects were investigated for one of the positions. Seven different wing-body configurations and a body-alone configuration were studied. The test was conducted at Mach numbers from 1.70 to 2.86 at angles of attack from about -4 deg to 24 deg. Pressure orifices were located at three longitudinal stations on each wing-body model, and at each station the orifices were located completely around the body, along the lower surface of the right wing (looking upstream), and along the upper surface of the left wing. All pressure coefficient data are tabulated and selected samples are shown graphically to illustrate the effects of the test variables. The effects of angle of attack, roll angle, Mach number, longitudinal station, wing vertical location, wing angular orientation, and wing-body juncture are analyzed. The vertical location of the wing on the body had a very strong effect on the body pressures. For a given angle of attack at a roll angle of 0 deg, the pressures were virtually constant in the spanwise direction across the windward surfaces of the wing-body combination. Pressure-relieving, channeling, and vortex effects were noted in the data.

Allen, Jerry M.↗