Strainer fits inside flared-tube fittings
Cylindrical wire-mesh strainer which fits inside flare-tube fittings is readily installed and easily replaced. It has a collar that seats on the tapered shoulder of the male fitting.
Parker, O. J.↗
SEARCH · Engineering Papers
Results for “Fitting”
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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The Effect of Various Surface Conditions on Press Fits of Steel Bushings and 17S-T Aluminum-alloy Fittings
Explore the source record for details and available documents.
FITTINGS↗
Automated Resonance Fitting for Nuclear Data Evaluation
Global and national efforts to deliver high-quality nuclear data to users have a wide-ranging impact, affecting applications in national security, reactor operations, basic science, medicine, and more. Cross section evaluation is a major part of this effort, combining theory and experimentation to produce recommended values and uncertainties for reaction probabilities. Resonance region evaluation is a specialized type of nuclear data evaluation that can require significant manual effort and months of time from expert scientists. In this article, non-convex non-linear optimization methods are combined with concepts of inferential statistics to infer a resonance model from experimental data in an automated manner that is not dependent on prior evaluation(s). This methodology aims to enhance the workflow of a resonance evaluator by minimizing time, effort, and the potential for bias from prior assumptions, while enhancing reproducibility and documentation, thereby addressing well-known challenges in the field.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations
This study evaluates the comparative performance of spatiotemporal fusion and time-series fitting methods for constructing high-spatiotemporal-resolution remote sensing time-series data. Due to in-class similarity of fusion methods and fitting methods, we employ the Fit-FC (Fitting, spatial Filtering, and residual Compensation) model as a representative fusion method and the linear harmonic fitting model as a representative fitting method. Both Fit-FC and the linear harmonic fitting are widely used for high-spatiotemporal-resolution time-series data construction, and we modify the original Fit-FC model to enable automatic time-series fusion. To ensure data representativeness, we use 3 years (2019–2021) of Harmonized Landsat and Sentinel-2 surface reflectance datasets and Terra MCD43A4 products. Eight experimental regions are selected worldwide to guarantee generalization of the comparative performance between fusion and fitting methods, covering diverse land-use types (cropland, developed land, forest, and grassland) and varying climatological conditions. Time-series of NDVI and surface reflectance are analyzed under both actual observations and simulated data-missing scenarios. The constructed time-series data reveals that (1) the modified Fit-FC and linear harmonic fitting model achieve excellent performance in constructing high-resolution time-series images; (2) the fusion method outperforms the fitting method in constructing time-series of NDVI and surface reflectance images in cropland-, forest-, and grassland-dominated regions; (3) both methods achieve comparable performance in developed-dominated regions; (4) the fusion method is more robust to missing data, and better captures abrupt phenological transitions under conditions of continuous missing data; (5) the fitting method is computationally more efficient, making it suitable for large-scale time-series image reconstruction. This study provides valuable insights for selecting optimal strategies to generate high-resolution time-series images across diverse application scenarios and lays a foundation for extensions to other vegetation indices or land surface variables.
54 ENVIRONMENTAL SCIENCES↗
Predictive models of the genetic bases underlying budding yeast fitness in multiple environments
Abstract The ability of organisms to adapt and survive depends on the effects of genes and the environment on fitness. However, the multigenic nature of fitness and genotype-by-environment interactions hinder our understanding of the genetic basis of fitness. Here, we established fitness prediction models for 35 environments using machine learning and existing fitness data and different genetic variant types for a Saccharomyces cerevisiae population. Models revealed that the predictive ability of genetic variants varied across environments, with copy number variants explaining the majority of fitness variation in most cases. Model interpretation showed that different variant types identified distinct gene sets associated with predictive variants. These gene sets were significantly enriched in experimentally validated genes affecting fitness in only a subset of environments, indicating that many genes influencing fitness remain unexplored. Notably, non-experimentally validated genes were more important than validated ones for fitness predictions. Gene contributions to predictions were both isolate- and environment-dependent, pointing to gene-by-gene and gene-by-environment interactions. Furthermore, models uncovered experimentally validated and novel candidate genetic interactions for a well-characterized stress, the fungicide benomyl. These findings highlight the feasibility of identifying the genetic basis of fitness by using different genetic variant types and offer novel targets for future functional analysis.
DNA copy number variations↗
Soft X-ray spectral fits of Geminga with model neutron star atmospheres
The spectrum of the soft X-ray pulsar Geminga consists of two components, a softer one which can be interpreted as thermal-like radiation from the surface of the neutron star, and a harder one interpreted as radiation from a polar cap heated by relativistic particles. We have fitted the soft spectrum using a detailed magnetized hydrogen atmosphere model. The fitting parameters are the hydrogen column density, the effective temperature T(sub eff), the gravitational redshift z, and the distance to radius ratio, for different values of the magnetic field B. The best fits for this model are obtained when B less than or approximately 1 x 10(exp 12) G and z lies on the upper boundary of the explored range (z = 0.45). The values of T(sub eff) approximately = (2-3) x 10(exp 5) K are a factor of 2-3 times lower than the value of T(sub eff) obtained for blackbody fits with the same z. The lower T(sub eff) increases the compatibility with some proposed schemes for fast neutrino cooling of neutron stars (NSs) by the direct Urca process or by exotic matter, but conventional cooling cannot be excluded. The hydrogen atmosphere fits also imply a smaller distance to Geminga than that inferred from a blackbody fit. An accurate evaluation of the distance would require a better knowledge of the ROSAT Position Sensitive Proportional Counter (PSPC) response to the low-energy region of the incident spectrum. Our modeling of the soft component with a cooler magnetized atmosphere also implies that the hard-component fit requires a characteristic temperature which is higher (by a factor of approximately 2-3) and a surface area which is smaller (by a factor of 10(exp 3), compared to previous blackbody fits.
Meyer, R. D.↗
Estimating errors in least-squares fitting
While least-squares fitting procedures are commonly used in data analysis and are extensively discussed in the literature devoted to this subject, the proper assessment of errors resulting from such fits has received relatively little attention. The present work considers statistical errors in the fitted parameters, as well as in the values of the fitted function itself, resulting from random errors in the data. Expressions are derived for the standard error of the fit, as a function of the independent variable, for the general nonlinear and linear fitting problems. Additionally, closed-form expressions are derived for some examples commonly encountered in the scientific and engineering fields, namely ordinary polynomial and Gaussian fitting functions. These results have direct application to the assessment of the antenna gain and system temperature characteristics, in addition to a broad range of problems in data analysis. The effects of the nature of the data and the choice of fitting function on the ability to accurately model the system under study are discussed, and some general rules are deduced to assist workers intent on maximizing the amount of information obtained form a given set of measurements.
Richter, P. H.↗
Resistance of virus to extinction on bottleneck passages: study of a decaying and fluctuating pattern of fitness loss
RNA viruses display high mutation rates and their populations replicate as dynamic and complex mutant distributions, termed viral quasispecies. Repeated genetic bottlenecks, which experimentally are carried out through serial plaque-to-plaque transfers of the virus, lead to fitness decrease (measured here as diminished capacity to produce infectious progeny). Here we report an analysis of fitness evolution of several low fitness foot-and-mouth disease virus clones subjected to 50 plaque-to-plaque transfers. Unexpectedly, fitness decrease, rather than being continuous and monotonic, displayed a fluctuating pattern, which was influenced by both the virus and the state of the host cell as shown by effects of recent cell passage history. The amplitude of the fluctuations increased as fitness decreased, resulting in a remarkable resistance of virus to extinction. Whereas the frequency distribution of fitness in control (independent) experiments follows a log-normal distribution, the probability of fitness values in the evolving bottlenecked populations fitted a Weibull distribution. We suggest that multiple functions of viral genomic RNA and its encoded proteins, subjected to high mutational pressure, interact with cellular components to produce this nontrivial, fluctuating pattern.
Serial Passage↗
Changes in peak oxygen uptake and plasma volume in fit and unfit subjects following exposure to a simulation of microgravity
To test the hypothesis that the magnitude of reduction in plasma volume and work capacity following exposure to simulated microgravity is dependent on the initial level of aerobic fitness, peak oxygen uptake (VO2peak) was measured in a group of physically fit subjects and compared with VO2peak in a group of relatively unfit subjects before and after 10 days of continuous 6 degrees head-down tilt (HDT). Ten fit subjects (40 +/- 2 year) with mean +/- SE VO2peak = 48.9 +/- 1.7 mL kg-1 min-1 were matched for age, height, and lean body weight with 10 unfit subjects (VO2peak = 37.7 +/- 1.6 mL kg-1 min-1). Before and after HDT, plasma, blood, and red cell volumes and body composition were measured and all subjects underwent a graded supine cycle ergometer test to determine VO2peak period needed. Reduced VO2peak in fit subjects (-16.2%) was greater than that of unfit subjects (-6.1%). Similarly, reductions in plasma (-18.3%) and blood volumes (-16.0%) in fit subjects were larger than those of unfit subjects (blood volume = -5.6%; plasma volume = -6.6%). Reduced plasma volume was associated with greater negative body fluid balance during the initial 24 h of HDT in the fit group (912 +/- 154 mL) compared with unfit subjects (453 +/- 200 mL). The percentage change for VO2peak correlated with percentage change in plasma volume (r = +0.79). Following exposure to simulated microgravity, fit subjects demonstrated larger reductions in VO2peak than unfit subjects which was associated with larger reductions in plasma and blood volume. These data suggest that the magnitude of physical deconditioning induced by exposure to microgravity without intervention of countermeasures was influenced by the initial fitness of the subjects.
Non-NASA Center↗
Expandable Purge Chambers Would Protect Cryogenic Fittings
Expandable ice-prevention and cleanliness-preservation (EIP-CP) chambers have been proposed to prevent the accumulation of ice or airborne particles on quick-disconnect (QD) fittings, or on ducts or tubes that contain cryogenic fluids. In the original application for which the EIP-CP chambers were conceived, there is a requirement to be able to disconnect and reconnect the QD fittings in rapid succession. If ice were to form on the fittings by condensation and freezing of airborne water vapor on the cold fitting surfaces, the ice could interfere with proper mating of the fittings, making it necessary to wait an unacceptably long time for the ice to thaw before attempting reconnection. By keeping water vapor away from the cold fitting surfaces, the EIP-CP chambers would prevent accumulation of ice, preserving the ability to reconnect as soon as required. Basically, the role of an EIP-CP chamber would be to serve as an enclosure for a flow of dry nitrogen gas that would keep ambient air away from QD cryogenic fittings. An EIP-CP chamber would be an inflatable device made of a fabriclike material. The chamber would be attached to an umbilical plate holding a cryogenic QD fitting.
Townsend, Ivan I., III↗
Framework for X-ray mirror surface shape fitting
For accurate characterization of grazing-incidence X-ray mirrors, we present a comprehensive framework to fit measured surface shapes (either slope or height) of X-ray mirrors used in synchrotron radiation and free-electron laser facilities. We summarize the closed-form expressions of some typical surface shapes of X-ray mirrors including elliptic cylinders, hyperbolic cylinders, ellipsoids, hyperboloids, and diaboloids. This framework is composed of four layers: definition of standard shapes with closed-form expressions, generation of theoretical surface with pose parameters (six degrees of freedom defining an object's position and orientation relative to a coordinate system), parameter optimization with the ability to select which parameters are fit and which are held constant, and the development of user-friendly fitting function wrappers for particular fitting tasks. A few practical fitting examples are demonstrated to verify the effectiveness of the proposed fitting framework. We discuss the physical meanings of the fitting parameters, and provide several examples using the elliptic cylinder and ellipsoid shapes to highlight some features of the framework. Moreover, we provide the presented framework as open-source codes (MATLAB and Python codes available at https://github.com/nsls2omf/xmf) to the community to encourage academic collaboration and further improvements.
36 MATERIALS SCIENCE↗
Knowledge Graph of RB-Tnseq Data from Fitness Browser (KP-DP1)
Motivation: Predicting microbial gene fitness across environmental conditions remains a central challenge for predictive phenomics and autonomous experimentation. Fitness assays generate large volumes of genotype–phenotype measurements difficult to integrate with experimental metadata and biological function in a form that supports mechanistic reasoning. Knowledge graphs offer a semantic framework for unifying modalities and enabling context-aware inference. Results: We build GIMME (Graph Inference for Microbial Metabolism Exploration), a semantically grounded knowledge graph that unifies gene fitness measurements spanning 10 Pseudomonas species with experimental metadata and biological context. Media are decomposed into chemical components and experiments carry structured links to natural-language descriptions. The resulting graph supports two inference modes: (1) symbolic graph traversal to surface candidate gene–environment and gene–chemical associations, and (2) learned inference using heterogeneous graph neural networks that propagate information across neighborhoods. We formulate link regression over (gene, media, experiment) triplets, combining learned gene embeddings with pretrained LLM sourced text embeddings of node descriptions to predict gene fitness. We then augment a baseline MLP with an auxiliary message-passing encoder (GraphSAGE/GAT) that propagates information over gene–protein–function and media–chemical subgraphs, and fuse the two pathways with a gated residual connection. This approach produces strong agreement with held-out fitness measurements (GraphSAGE Pearson r 0.74) while also highlighting inference challenges in extreme-fitness regimes. We aggregate GAT edge-attention weights by relation type and layer to estimate which biological and environmental relations most influence fitness predictions. Conclusion: This work explores using knowledge graphs as “context graphs” for microbial phenotype prediction. They provide a rich substrate which enables explainable retrieval of supporting evidence, and provides a natural bridge to autonomous workflows that prioritize the next experiment.
59 BASIC BIOLOGICAL SCIENCES↗
Methods of Achieving and Maintaining Physical Fitness for Prolonged Space Flight
This final summary report covers the five experiments that were conducted over a 24-month period beginning May 1, 1967 and ending April 30, 1969. Experiment I revealed that running and riding a bicycle ergometer produced similar gains in physical fitness variables. In Experiment I the subjects exercising at a 180 heart rate made a greater improvement in physical fitness than did those exercising a t a 140 or 160 heart rate. In Experiment II the subjects who exercised sixty minutes per day made greater gains on specified components of physical fitness than did those who exercised twenty or forty minutes per day, twelve times per week made greater gains on specified components of physical fitness than did those who exercised three or six times per week. In Experiment V, it was found that subjects could maintain a moderate level of fitness by exercising at a pulse rate of 160 beats per minute for twenty-minute periods three times per week, that subjects who "overtrained" by exercising twice daily to near exhaustion increased in fitness and that those subjects who discontinued training decreased in fitness.
Olree, Harry D.↗
Simplified curve fits for the thermodynamic properties of equilibrium air
New, improved curve fits for the thermodynamic properties of equilibrium air have been developed. The curve fits are for pressure, speed of sound, temperature, entropy, enthalpy, density, and internal energy. These curve fits can be readily incorporated into new or existing computational fluid dynamics codes if real gas effects are desired. The curve fits are constructed from Grabau-type transition functions to model the thermodynamic surfaces in a piecewise manner. The accuracies and continuity of these curve fits are substantially improved over those of previous curve fits. These improvements are due to the incorporation of a small number of additional terms in the approximating polynomials and careful choices of the transition functions. The ranges of validity of the new curve fits are temperatures up to 25 000 K and densities from 10 to the -7 to 10 to the 3d power amagats.
Srinivasan, S.↗
Simplified curve fits for the thermodynamic properties of equilibrium air
New improved curve fits for the thermodynamic properties of equilibrium air were developed. The curve fits are for p = p(e,rho), a = a(e,rho), T = T(e,rho), s = s(e,rho), T = T(p,rho), h = h(p,rho), rho = rho(p,s), e = e(p,s) and a = a(p,s). These curve fits can be readily incorporated into new or existing Computational Fluid Dynamics (CFD) codes if real-gas effects are desired. The curve fits were constructed using Grabau-type transition functions to model the thermodynamic surfaces in a piecewise manner. The accuracies and continuity of these curve fits are substantially improved over those of previous curve fits appearing in NASA CR-2470. These improvements were due to the incorporation of a small number of additional terms in the approximating polynomials and careful choices of the transition functions. The ranges of validity of the new curve fits are temperatures up to 25,000 K and densities from 10 to the minus 7th to 100 amagats (rho/rho sub 0).
Srinivasan, S.↗
Microconical interface fitting and interface grasping tool
A small and light weight microconical interface fitting may be attached to the surface of a space vehicle or equipment to provide an attachment device for an astronaut or robot to capture the space vehicle or equipment. The microconical interface fitting of the present invention has an axisymmetrical conical body having a base portion with a torque reaction surface for preventing rotation of the interface grasping tool; a cavitated, sunken or hollowed out intermediate locking portion which has a cavity shaped for receiving the latches of the grasping tool and an upper guiding portion for guiding the grasping tool into axial alignment with the microconical interface fitting. The capture is accomplished with an interface grasping tool. The grasping tool comprises an outer sleeve with a handle attached, an inner sleeve which may be raised and lowered within the outer sleeve with a plurality of latches supported at the lower end and a cam to raise and lower the inner sleeve. When the inner sleeve is at its lowest position, the latches form the largest diameter opening for surrounding the microconical fitting and the latches form the smallest diameter or a locking, grasping position when raised to the highest position within the outer sleeve. The inner sleeve may be at an intermediate, capture position which permits the latches to be biased outwardly when contacting the microconical fitting under very low forces to grasp the fitting and permits capture (soft docking) without exact alignment of the fitting and the tool.
Gernhardt, Michael L.↗
Measurements of three-flavor neutrino oscillations from a PISCES two-detector fit to the NOvA Experiment data
NOvA is a long-baseline neutrino oscillation experiment with two functionally identical detectors: a Near Detector (ND) at Fermilab, placed 1 km from the neutrino source, and a Far Detector (FD) located 810 km away from the ND in Minnesota. NOvA s primary physics goals are to measure the neutrino oscillation parameters $\theta_{23}$ and $\Delta m^2_{32}$ with high precision, determine the neutrino mass hierarchy, and constrain the value of $\delta_{CP}$, primarily via the study of muon neutrino to electron neutrino oscillation. Extracting values for oscillation parameters from fits to data usually relies on treating systematic uncertainties as nuisance parameters, a strategy that suffers from poor scalability as the number of uncertainties becomes larger. This work introduces PISCES (Parameter Inference with Systematic Covariance and Exact Statistics), a novel method that circumvents this scalability problem by encoding systematic uncertainties into a covariance matrix. PISCES utilizes a nested minimization in which optimal systematic pulls are first computed using the covariance matrix in an inner minimization step, then the oscillation parameters are profiled over in the outer minimization. PISCES also uses a Poisson Likelihood term, making it ideal for the inclusion of low-statistic samples in the fits. PISCES is a flexible framework that also supports complex fits, such as a joint Near and Far detector fit. In the standard NOvA analysis, oscillation parameters are extracted using an extrapolation technique in which the ND data indirectly constrain the FD prediction via a ratio method. PISCES, on the other hand, enables a simultaneous ND+FD fit, allowing the high-statistics ND data to directly constrain systematic uncertainties across all samples. This thesis presents the full PISCES joint ND+FD fit for the NOvA three-flavor analysis, details its implementation, and evaluates its performance through extensive robustness tests and fake data studies. It also provides a comparison between the PISCES joint ND+FD results and the standard NOvA extrapolation method using the full NOvA 10-year data set. The results demonstrate that PISCES can successfully fit NOvA data while incorporating the constraints from the ND detectors consistently, using physically motivated systematic uncertainties to account for data/MC discrepancies.
Rajaoalisoa, Miriama [Cincinnati U.]↗
Fitting Polynomial Equations to Curves and Surfaces
FIT is computer program for interactively determining least-squares polynomial equations that fit user-supplied data. Finds leastsquares fits for functions of two independent variables. Interactive graphical and editing capabilities in FIT enables user to control polynomial equations to be fitted to data arising from most practical applications. FIT written in FORTRAN and COMPASS.
Arbuckle, P. D.↗