Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “prediction methods”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Analysis of nonlifting and lifting airfoils in transonic flow by parametric differentiation

A method is presented which allows one to solve nonlinear transonic flow problems by analyzing a sequence of linear equations. The small disturbance formulation of steady transonic flow over airfoils is linearized by considering the perturbations due to small changes in airfoil thickness ratio and angle of attack. Repeatedly incrementing those parameters results in a series of nonlinear solutions and cumulatively determines the effects of large changes in airfoil geometry. Successive line overrelaxation is used to solve the associated linear equations and is coupled with predictor-corrector methods to yield series of nonlinear solutions. Computed pressure distributions on biconvex airfoils show good agreement with experimental data and other transonic prediction methods. Possible extensions to unsteady and/or three-dimensional transonic flow problems are briefly discussed.

Whitlow, W., Jr.↗
NASA NTRS1982

Lagrangian least-squares prediction of solar activity

Statistical prediction methods for short-term (months) and long-term (years) forecasting of solar activity were studied. The comparisons indicate that better predictions, in a chi square sense, are possible by lining up the maximum (or minimums, or both) by cycle number. Evidence is also presented to support the existence of an aperiodic variation in the periods as well as the amplitudes.

Holland, R. L.↗
NASA NTRS2014

Initial Evaluations of LoC Prediction Algorithms Using the NASA Vertical Motion Simulator

Flying near the edge of the safe operating envelope is an inherently unsafe proposition. Edge of the envelope here implies that small changes or disturbances in system state or system dynamics can take the system out of the safe envelope in a short time and could result in loss-of-control events. This study evaluated approaches to predicting loss-of-control safety margins as the aircraft gets closer to the edge of the safe operating envelope. The goal of the approach is to provide the pilot aural, visual, and tactile cues focused on maintaining the pilot's control action within predicted loss-of-control boundaries. Our predictive architecture combines quantitative loss-of-control boundaries, an adaptive prediction method to estimate in real-time Markov model parameters and associated stability margins, and a real-time data-based predictive control margins estimation algorithm. The combined architecture is applied to a nonlinear transport class aircraft. Evaluations of various feedback cues using both test and commercial pilots in the NASA Ames Vertical Motion-base Simulator (VMS) were conducted in the summer of 2013. The paper presents results of this evaluation focused on effectiveness of these approaches and the cues in preventing the pilots from entering a loss-of-control event.

Pilot Cue↗
NASA NTRS2015

Failure Predictions of Out-of-Autoclave Sandwich Joints with Delaminations under Flexure Loads

An analysis and a test program was conducted to investigate the damage tolerance of composite sandwich joints. The joints contained a single circular delamination between the face-sheet and the doubler. The coupons were fabricated through out-of-autoclave (OOA) processes, a technology NASA is investigating for joining large composite sections. The four-point bend flexure test was used to induce compression loading into the side of the joint where the delamination was placed. The compression side was chosen since it tends to be one of the most critical loads in launch vehicles. Autoclave cure was used to manufacture the composite sandwich sections, while the doubler was co-bonded onto the sandwich face-sheet using an OOA process after sandwich panels were cured. A building block approach was adopted to characterize the mechanical properties of the joint material, including the fracture toughness between the doubler and facesheet. Twelve four-point-bend samples were tested, six in the sandwich core ribbon orientation and six in sandwich core cross-ribbon direction. Analysis predicted failure initiation and propagation at the pre-delaminated location, consistent with experimental observations. A building block approach using fracture analyses methods predicted failure loads in close agreement with tests. This investigation demonstrated a small strength reduction due to a flaw of significant size compared to the width of the sample. Therefore, concerns of bonding an OOA material to an in-autoclave material was mitigated for the geometries, materials, and load configurations considered.

Damage↗
NASA NTRS2015

Failure Predictions of Out-of-Autoclave Sandwich Joints with Delaminations Under Flexure Loads

An analysis and a test program was conducted to investigate the damage tolerance of composite sandwich joints. The joints contained a single circular delamination between the face-sheet and the doubler. The coupons were fabricated through out-of-autoclave (OOA) processes, a technology NASA is investigating for joining large composite sections. The four-point bend flexure test was used to induce compression loading into the side of the joint where the delamination was placed. The compression side was chosen since it tends to be one of the most critical loads in launch vehicles. Autoclave cure was used to manufacture the composite sandwich sections, while the doubler was co-bonded onto the sandwich face-sheet using an OOA process after sandwich panels were cured. A building block approach was adopted to characterize the mechanical properties of the joint material, including the fracture toughness between the doubler and face-sheet. Twelve four-point-bend samples were tested, six in the sandwich core ribbon orientation and six in sandwich core cross-ribbon direction. Analysis predicted failure initiation and propagation at the pre-delaminated location, consistent with experimental observations. A building block approach using fracture analyses methods predicted failure loads in close agreement with tests. This investigation demonstrated a small strength reduction due to a flaw of significant size compared to the width of the sample. Therefore, concerns of bonding an OOA material to an in-autoclave material was mitigated for the geometries, materials, and load configurations considered.

Tolerance↗
NASA NTRS1990

Prediction of vortex shedding from forebodies with chines

An engineering prediction method to calculate vortex shedding from noncircular forebodies with sharp chine edges in subsonic flow at large incidence angles is presented. The forebody is represented by two- and three-dimensional singularities, and the lee side vortex wake is modeled by discrete vortices in crossflow planes along the body. The computational procedure is described, and comparisons of measured and predicted surface pressure distributions and predicted flow field vectors are presented to illustrate the method.

Mendenhall, Michael R.↗
DOE OSTI2021

Implicit-Explicit Multirate Infinitesimal GARK Methods

This work focuses on the development of a new class of high-order accurate methods for multirate time integration of systems of ordinary differential equations. Unlike other recent work in this area, the proposed methods support mixed implicit-explicit (IMEX) treatment of the slow time scale. In addition to allowing this slow time scale flexibility, the proposed methods utilize a so-called infinitesimal formulation for the fast time scale through definition of a sequence of modified “fast" initial-value problems that may be solved using any viable algorithm. We name the proposed class as implicit-explicit multirate infinitesimal generalized-structure additive Runge--Kutta (IMEX-MRI-GARK) methods. In addition to defining these methods, we prove that they may be viewed as specific instances of GARK methods and derive a set of order conditions on the IMEX-MRI-GARK coefficients to guarantee both third and fourth order accuracy for the overall multirate method. Additionally, we provide three specific IMEX-MRI-GARK methods, two of order three and one of order four. We conclude with numerical simulations on two multirate test problems, demonstrating the methods' predicted convergence rates and comparing their efficiency against both legacy IMEX multirate schemes and recent third and fourth order implicit MRI-GARK methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

The use of high-resolution terrain data in gravity field prediction

Different types of gravity prediction methods for local and regional gravity evaluation are developed, tested, and compared. Four different test areas were particularly selected in view of different prediction requirements. Also different parts of the spectrum of the gravity field were considered.

Groten, E.↗
NASA NTRS1990

Computational rotorcraft flowfield research at the U.S. Army AeroStructures Directorate

Rotorcraft aerodynamic interaction investigations conducted experimentally and computationally by the U.S. Army at the NASA Langley subsonic tunnel are described. Consideration is given to fuselage velocity computation, an interactional aerodynamics method, a rotor/wake/fuselage method, predicted wake geometry, views of tip vortex trajectory, and an inflow velocity study. Calculations were found to predict the periodic geometry of a rotor wake. Details of its interactions with the fuselage surface are not well modeled with inviscid panel methods. For the cases investigated in the present study, the overall effects of the fuselage are relatively small. However, increasing the size of the fuselage or decreasing the fuselage-rotor space will amplify these effects.

Berry, John D.↗
DOE OSTI2020

Frequency and Time Domain Nuclear-Electronic Orbital Equation-of-Motion Coupled Cluster Methods: Combination Bands and Electronic-Protonic Double Excitations

The accurate description of excited vibronic states is important for modeling a wide range of photoinduced processes. The nuclear-electronic orbital (NEO) approach, which treats specified protons on the same level as the electrons, can describe excited electronic-protonic states. Herein the multicomponent equation-of-motion coupled cluster with singles and doubles (NEO-EOM-CCSD) method and its time-domain counterpart, TD-NEO-EOM-CCSD, are developed and implemented. The application of these methods to the HCN molecule highlights their capabilities. These methods predict qualitatively reasonable energies and intensities for a combination band corresponding to simultaneous excitation of two vibrational modes, as well as an overtone. These methods also describe states with double excitation character, such as excited electronic-protonic states corresponding to the simultaneous excitation of an electron and a proton. The ability of the NEO-EOM-CCSD method and its time-dependent counterpart to describe combination bands, overtones, and double excitations will enable a wide range of photochemical applications.

Pavosevic, Fabijan↗
NASA NTRS1984

Lagrangian least-squares prediction of solar flux (F-bar 10.7)

The result of a study on the application of an improved statistical prediction method for estimating the intermediate-term (months) and long-term (years) behavior of solar flux is discussed. The study indicates that better predictions, in a chi square sense, are possible by selecting sets of the solar flux data such that each set (cycle) starts and ends at the maxima (or minima) for the data base and initialization point of the procedure. Then one applies a Lagrangian least-squares statistical technique. Evidence is also presented to support the existence of an aperiodic variation in the periods as well as the amplitudes.

Holland, R. L.↗
NASA NTRS1995

Predictions of LDEF radioactivity and comparison with measurements

As part of the program to utilize LDEF data for evaluation and improvement of current ionizing radiation environmental models and related predictive methods for future LEO missions, calculations have been carried out to compare with the induced radioactivity measured in metal samples placed on LDEF. The predicted activation is about a factor of two lower than observed, which is attributed to deficiencies in the AP8 trapped proton model. It is shown that this finding based on activation sample data is consistent with comparisons made with other LDEF activation and dose data. Plans for confirming these results utilizing additional LDEF data sets, and plans for model modifications to improve the agreement with LDEF data, are discussed.

Armstrong, T. W.↗
NASA NTRS2001

Impacts of Interannual Climate Variability on Agricultural and Marine Ecosystems

The El Nino - Southern Oscillation (ENSO) is the dominant mode of global interannual climate variability, and seems to be the only mode for which current prediction methods are more skillful than climatology or persistence. The Zebiak and Cane intermediate coupled ocean-atmosphere model has been in use for ENSO prediction for more than a decade, with notable success. However, the sole dependence of its original initialization scheme and the improved initialization on wind fields derived from merchant ship observations proved to be a liability during 1997/1998 El Nino event: the deficiencies of wind observations prevented the oceanic component of the model from reaching the realistic state during the year prior to the event, and the forecast failed. Our work on the project was concentrated on the use of satellite data for improving various stages of ENSO prediction technology: model initialization, bias correction, and data assimilation. Close collaboration with other teams of the IDS project was maintained throughout.

Cane, M. A.↗
NASA NTRS2006

Development of a Liner Design Methodology and Relevant Results of Acoustic Suppression in the Farfield for Mixer-Ejector Nozzles

We have developed a process to predict noise field interior to the ejector and in the farfield for any liner design for a mixer-ejector of arbitrary scale factor. However, a number of assumptions, not verified for the current application, utilized in this process, introduce uncertainties in the final result, especially, on a quantitative basis. The normal impedance model for bulk with perforated facesheet is based on homogeneous foam materials of low resistivity. The impact of flow conditions for HSCT application as well as the impact of perforated facesheet on predicted impedance is not properly accounted. Based on the measured normal impedance for deeper bulk samples (i.e., 2.0 in.) the predicted reactance is much higher compared to the data at frequencies above 2 kHz for T-foam and 200 ppi SiC. The resistance is under predicted at lower frequencies (below 4 kHz) for these samples. Thus, the use of such predicted data in acoustic suppression is likely to introduce inaccuracies. It should be noted that the impedance prediction methods developed recently under liner technology program are not utilized in the studies described in this report due to the program closeout. Acoustic suppression prediction is based on the uniform flow and temperature conditions in a two-sided treated constant area rectangular duct. In addition, assumptions of equal energy per mode noise field and interaction of all frequencies with the treated surface for the entire ejector length may not be accurate. While, the use of acoustic transfer factor minimizes the inaccuracies associated with the prediction for a known test case, the assumption of the same factor for other liner designs and with different linear scale factor ejectors seems to be very optimistic. As illustrated in appendix D that the predicted noise suppression for LSM-1 is lower compared to the measured data is an indication of the above argument. However, the process seems to be more reliable when used for the same scale models for different liner designs as demonstrated for Gen. 1 mixer-ejectors.

Salikuddin, M.↗
NASA NTRS1981

Development and validation of the V/STOL aerodynamics and stability and control manual

A V/STOL Aerodynamics and Stability and Control Manual was developed to provide prediction methods which are applicable to a wide range of V/STOL configurations in hover and transition flight, in and out of ground effect. Propulsion-induced effects have been combined with unpowered aerodynamics in a buildup of total forces and moments for the jet-lift concept, so that total aerodynamics can be used to predict aircraft stability, control, and flying qualities characteristics. Results of longitudinal aerodynamic predictions have been compared with test data, and indicate that the methods are fast, inexpensive, and within the desired accuracy for the objective preliminary design stage.

Henderson, C.↗
DOE OSTI2023

Reducing Uncertainty in Offshore Wind Energy Yield Estimates via a Metocean Reference Site

The offshore wind industry is burgeoning in the coastal waters of the United States, specifically along the Atlantic. For wind energy to be successful, reliable observations and model simulations are needed for resource assessment and forecasting. While many of these activities have already begun, there is currently an absence of observations at hub-height in these waters, with the closest available hub-height measurements usually taken onshore. Deployment of floating lidars has occurred through various federally funded projects, but only encapsulates time periods of a couple of years at best. Private industry is also beginning to leverage floating lidars, but this data is often proprietary, and not shared with the general public. In this work, we make the case for a metocean reference site for long-term offshore wind energy. Specifically, we quantify the impact of having a metocean reference site compared to other methods of determining hub-height winds and energy production. We use an offshore floating lidar to directly measure the wind resource, and compare these measurements to predictions derived from other widely-available surface meteorological variables. These prediction methods (vertical extrapolation, machine learning, and NWP output) produce a variety of vertical wind speed profiles, of which produce different energy yield estimates for a reference offshore turbine (Figure 1). While some methods perform reasonably well against the lidar, the uncertainty in these energy yield estimates has financial implications, further illustrating the need for long-term measurements in coastal waters.

machine learning↗
DOE OSTI2021

Predicting Intensive Care Unit Length of Stay and Mortality Using Patient Vital Signs: Machine Learning Model Development and Validation

Background: Patient monitoring is vital in all stages of care. In particular, intensive care unit (ICU) patient monitoring has the potential to reduce complications and morbidity, and to increase the quality of care by enabling hospitals to deliver higher-quality, cost-effective patient care, and improve the quality of medical services in the ICU. Objective: We here report the development and validation of ICU length of stay and mortality prediction models. The models will be used in an intelligent ICU patient monitoring module of an Intelligent Remote Patient Monitoring (IRPM) framework that monitors the health status of patients, and generates timely alerts, maneuver guidance, or reports when adverse medical conditions are predicted. Methods: We utilized the publicly available Medical Information Mart for Intensive Care (MIMIC) database to extract ICU stay data for adult patients to build two prediction models: one for mortality prediction and another for ICU length of stay. For the mortality model, we applied six commonly used machine learning (ML) binary classification algorithms for predicting the discharge status (survived or not). For the length of stay model, we applied the same six ML algorithms for binary classification using the median patient population ICU stay of 2.64 days. For the regression-based classification, we used two ML algorithms for predicting the number of days. We built two variations of each prediction model: one using 12 baseline demographic and vital sign features, and the other based on our proposed quantiles approach, in which we use 21 extra features engineered from the baseline vital sign features, including their modified means, standard deviations, and quantile percentages. Results: We could perform predictive modeling with minimal features while maintaining reasonable performance using the quantiles approach. The best accuracy achieved in the mortality model was approximately 89% using the random forest algorithm. The highest accuracy achieved in the length of stay model, based on the population median ICU stay (2.64 days), was approximately 65% using the random forest algorithm. Conclusions: The novelty in our approach is that we built models to predict ICU length of stay and mortality with reasonable accuracy based on a combination of ML and the quantiles approach that utilizes only vital signs available from the patient’s profile without the need to use any external features. This approach is based on feature engineering of the vital signs by including their modified means, standard deviations, and quantile percentages of the original features, which provided a richer dataset to achieve better predictive power in our models.

59 BASIC BIOLOGICAL SCIENCES↗