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NASA NTRS2011

AN Fitting Reconditioning Tool

A tool was developed to repair or replace AN fittings on the shuttle external tank (ET). (The AN thread is a type of fitting used to connect flexible hoses and rigid metal tubing that carry fluid. It is a U.S. military-derived specification agreed upon by the Army and Navy, hence AN.) The tool is used on a drill and is guided by a pilot shaft that follows the inside bore. The cutting edge of the tool is a standard-size replaceable insert. In the typical Post Launch Maintenance/Repair process for the AN fittings, the six fittings are removed from the ET's GUCP (ground umbilical carrier plate) for reconditioning. The fittings are inspected for damage to the sealing surface per standard operations maintenance instructions. When damage is found on the sealing surface, the condition is documented. A new AN reconditioning tool is set up to cut and remove the surface damage. It is then inspected to verify the fitting still meets drawing requirements. The tool features a cone-shaped interior at 36.5 , and may be adjusted at a precise angle with go-no-go gauges to insure that the cutting edge could be adjusted as it wore down. One tool, one setting block, and one go-no-go gauge were fabricated. At the time of this reporting, the tool has reconditioned/returned to spec 36 AN fittings with 100-percent success of no leakage. This tool provides a quick solution to repair a leaky AN fitting. The tool could easily be modified with different-sized pilot shafts to different-sized fittings.

Lopez, Jason↗

NASA NTRS2010

A New Compression Method for FITS Tables

As the size and number of FITS binary tables generated by astronomical observatories increases, so does the need for a more efficient compression method to reduce the amount disk space and network bandwidth required to archive and down1oad the data tables. We have developed a new compression method for FITS binary tables that is modeled after the FITS tiled-image compression compression convention that has been in use for the past decade. Tests of this new method on a sample of FITS binary tables from a variety of current missions show that on average this new compression technique saves about 50% more disk space than when simply compressing the whole FITS file with gzip. Other advantages of this method are (1) the compressed FITS table is itself a valid FITS table, (2) the FITS headers remain uncompressed, thus allowing rapid read and write access to the keyword values, and (3) in the common case where the FITS file contains multiple tables, each table is compressed separately and may be accessed without having to uncompress the whole file.

Pence, William↗

DOE OSTI2024

Automatic fitting of multiple-field solid-state NMR spectra

The NMR lineshapes produced by half-integer quadrupolar nuclei are sensitive to 11 distinct fit parameters per inequivalent site. To date, automatic fitting routines have failed to replace manual parameter insertion and evaluation due to the importance of local minima and the need for fitting multiple-field magic-angle spinning (MAS) and static spectra simultaneously. Herein we introduce a new tool, AMES-Fit (Automatic Multiple Experiment Simulation and Fitting), to automatically find the global best-fit simulation parameters for a series of multiple-field NMR lineshapes. AMES-Fit uses an adaptive step size random search algorithm to dynamically probe parameter space and requires minimal human input. Importantly, the best fits are obtained in a few minutes of computation time that would otherwise have required several person-hours of work. The program is freely available and open-source.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Molecular-field-theory fits to magnetic susceptibilities of antiferromagnetic GdCu 2 Si 2 , CuO, LiCrO 2 , and α-CaCr 2 O 4 single crystals below their Néel temperatures

A recently-developed molecular field theory (MFT) has been used to fit single-crystal magnetic susceptibility χ versus temperature T data below the respective antiferromagnetic ordering temperature T N for a variety of collinear and coplanar noncollinear Heisenberg antiferromagnets. The spins in the system are assumed to interact by Heisenberg exchange and to be identical and crystallographically equivalent. The fitting parameters for χ(T ) of collinear antiferromagnets are measurable quantities: the Weiss temperature θ p in the Curie-Weiss law, TN, χ(T N ), and the spin S. For coplanar noncollinear helix and cycloid structures, an additional fitting parameter is the turn angle between layers of ferromagnetically-aligned spins. Here MFT fits to anisotropic χ(T) data from the literature for single crystals of the collinear antiferromagnets GdCu 2 Si 2 and CuO and the noncollinear antiferromagnets LiCrO 2 with a 120° cycloidal structure and α-CaCr 2 O 4 with a 120° helical structure below their respective N´eel temperatures are presented. The MFT fit to the anisotropic χ(T ≤ T N ) data for CuO is poor, whereas the fits to the data for GdCu 2 Si 2 , LiCrO 2 , and α-CaCr 2 O 4 are quite good. The poor fit for CuO is attributed to the influence of strong quantum fluctuations associated with the small Cu spin and the quasi-one-dimensional magnetism that are not taken into account by the MFT. The magnetic contribution to the zero-field heat capacity of the collinear antiferromagnet GdNiGe 3 at T ≤ T N is also fitted by the MFT.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Simulation and fitting of complex reaction network TPR: The key is the objective function

In this research, a method has been developed for finding improved fits during simulation and fitting of data from complex reaction network temperature programmed reactions (CRN-TPR). It was found that simulation and fitting of CRN-TPR presents additional challenges relative to simulation and fitting of simpler TPR systems. The method used here can enable checking the plausibility of proposed chemical mechanisms and kinetic models. The most important finding was that when choosing an objective function, use of an objective function that is based on integrated production provides more utility in finding improved fits when compared to an objective function based on the rate of production. The response surface produced by using the integrated production is monotonic, suppresses effects from experimental noise, requires fewer points to capture the response behavior, and can be simulated numerically with smaller errors. For CRN-TPR, there is increased importance (relative to simple reaction network TPR) in resolving of peaks prior to fitting, as well as from weighting of experimental data points. Using an implicit ordinary differential equation solver was found to be inadequate for simulating CRN-TPR. Lastly, the method employed here was capable of attaining improved fits in simulation and fitting of CRN-TPR when starting with a postulated mechanism and physically realistic initial guesses for the kinetic parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Curve fitting methods for solar radiation data modeling

This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R{sup 2}. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.

14 SOLAR ENERGY↗

DOE OSTI2014

Reversion and T Cell Escape Mutations Compensate the Fitness Loss of a CD8+ T Cell Escape Mutant in Their Cognate Transmitted/Founder Virus

Immune escape mutations that revert back to the consensus sequence frequently occur in newly HIV-1-infected individuals and have been thought to render the viruses more fit. However, their impact on viral fitness and their interaction with other immune escape mutations have not been evaluated in the background of their cognate transmitted/founder (T/F) viral genomes. To precisely determine the role of reversion mutations, we introduced reversion mutations alone or together with CD8+ T cell escape mutations in their unmodified cognate T/F viral genome and determined their impact on viral fitness in primary CD4+ T cells. Two reversion mutations, V247I and I64T, were identified in Gag and Tat, respectively, but neither had measurable effect on the fitness of their cognate T/F virus. The V247I and G248A mutations that were detected before and concurrently with the potent T cell escape mutation T242N, respectively, were selected by early T cell responses. The V247I or the G248A mutation alone partially restored the fitness loss caused by the T242N mutation. Together they could fully restore the fitness of the T242N mutant to the T/F level. These results demonstrate that the fitness loss caused by a T cell escape mutation could be compensated by preexisting or concurrent reversion and other T cell escape mutations. Our findings indicate that the overall viral fitness is modulated by the complex interplay among T cell escape, compensatory and reversion mutations to maintain the balance between immune escape and viral replication capacity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Statistical precision of the intensities retrieved from constrained fitting of overlapping peaks in high-resolution mass spectra

Least-squares fitting of overlapping peaks is often needed to separately quantify ions in high-resolution mass spectrometer data. A statistical simulation approach is used to assess the statistical precision of the retrieved peak intensities. The sensitivity of the fitted peak intensities to statistical noise due to ion counting is probed for synthetic data systems consisting of two overlapping ion peaks whose positions are pre-defined and fixed in the fitting procedure. The fitted intensities are sensitive to imperfections in the m/Q calibration. These propagate as a limiting precision in the fitted intensities that may greatly exceed the precision arising from counting statistics. The precision on the fitted peak intensity falls into one of three regimes. In the "counting-limited regime" (regime I), above a peak separation χ ~ 2 to 3 half-widths at half-maximum (HWHM), the intensity precision is similar to that due to counting error for an isolated ion. For smaller χ and higher ion counts (~ 1000 and higher), the intensity precision rapidly degrades as the peak separation is reduced ("calibration-limited regime", regime II). Alternatively for χ < 1.6 but lower ion counts (e.g. 10–100) the intensity precision is dominated by the additional ion count noise from the overlapping ion and is not affected by the imprecision in the m/Q calibration ("overlapping-limited regime", regime III). The transition between the counting and m/Q calibration-limited regimes is shown to be weakly dependent on resolving power and data spacing and can thus be approximated by a simple parameterisation based only on peak intensity ratios and separation. A simple equation can be used to find potentially problematic ion pairs when evaluating results from fitted spectra containing many ions. Longer integration times can improve the precision in regimes I and III, but a given ion pair can only be moved out of regime II through increased spectrometer resolving power. As a result, studies presenting data obtained from least-squares fitting procedures applied to mass spectral peaks should explicitly consider these limits on statistical precision.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1994

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.↗

NASA NTRS1995

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.↗

NASA NTRS2003

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↗

NASA NTRS1998

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↗

NASA NTRS2004

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↗

DOE OSTI2013

Non-linear Multidimensional Optimization for use in Wire Scanner Fitting

To ensure experiment efficiency and quality from the Continuous Electron Beam Accelerator at Jefferson Lab, beam energy, size, and position must be measured. Wire scanners are devices inserted into the beamline to produce measurements which are used to obtain beam properties. Extracting physical information from the wire scanner measurements begins by fitting Gaussian curves to the data. This study focuses on optimizing and automating this curve-fitting procedure. We use a hybrid approach combining the efficiency of Newton Conjugate Gradient (NCG) method with the global convergence of three nature-inspired (NI) optimization approaches: genetic algorithm, differential evolution, and particle-swarm. In this Python-implemented approach, augmenting the locally-convergent NCG with one of the globally-convergent methods ensures the quality, robustness, and automation of curve-fitting. After comparing the methods, we establish that given an initial data-derived guess, each finds a solution with the same chi-square- a measurement of the agreement of the fit to the data. NCG is the fastest method, so it is the first to attempt data-fitting. The curve-fitting procedure escalates to one of the globally-convergent NI methods only if NCG fails, thereby ensuring a successful fit. This method allows for the most optimal signal fit and can be easily applied to similar problems.

Terzic, Balsa↗

DOE OSTI2018

Avoiding erroneous analysis of MIM diode current-voltage characteristics through exponential fitting

Accurate fitting of measured current-voltage [$I$ ($V$) ] data is crucial to the correct analysis and understanding of metal-insulator–metal (MIM) diodes, especially for optical rectennas. With the commonly used polynomial fitting of the $I$$(V)$ data, the order of the fit can drastically affect the diode performance metrics such as resistance, responsivity, and asymmetry. Additionally, the resulting fitting coefficients provide no useful parameters. An exponential-based equation can fit the $I$$(V)$ data well, can avoid artifacts from the choice of order of the polynomial, and allows for the accurate calculation of diode performance metrics directly from the fitting coefficients. Finally, connecting the performance metrics to fitting coefficients shows a correspondence between zero-bias responsivity and asymmetry at any given voltage.

42 ENGINEERING↗

DOE OSTI2026

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↗

DOE OSTI2026

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↗

DOE OSTI2019

Fitting the strong coupling constant with soft-drop thrust

Soft drop has been shown to reduce hadronisation effects at $e^+e^-$ colliders for the thrust event shape. In this context, we perform fits of the strong coupling constant for the soft-drop thrust distribution at NLO+NLL accuracy to pseudo data generated by the Sherpa event generator. In particular, we focus on the impact of hadronisation corrections, which we estimate both with an analytical model and a Monte-Carlo based one, on the fitted value of $\alpha_s(m_Z)$. We find that grooming can reduce the size of the shift in the fitted value of $\alpha_s$ due to hadronisation. In addition, we also explore the possibility of extending the fitting range down to significantly lower values of (one minus) thrust. Here, soft drop is shown to play a crucial role, allowing us to maintain good fit qualities and stable values of the fitted strong coupling. The results of these studies show that soft-drop thrust is a promising candidate for fitting $\alpha_s$ at $e^+ e^-$ colliders with reduced impact of hadronisation effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗