Analysis methods to build contact networks from mobility data.
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A new method, based on partial spline models, is developed for including specified discontinuities in otherwise smooth two- and three-dimensional objective analyses. The method is appropriate for including tropopause height information in two- and three-dimensinal temperature analyses, using the O'Sullivan-Wahba physical variational method for analysis of satellite radiance data, and may in principle be used in a combined variational analysis of observed, forecast, and climate information. A numerical method for its implementation is described and a prototype two-dimensional analysis based on simulated radiosonde and tropopause height data is shown. The method may also be appropriate for other geophysical problems, such as modeling the ocean thermocline, fronts, discontinuities, etc.
There are multiple federal directives that Los Alamos National Laboratory (LANL) must follow for the proper implementation of quality assurance, strategic planning, and execution of manufacturing and surveillance operations. Recent assessments identified that manufacturing in all processing areas is dynamic due to influencing scope changes, design modifications, funding adjustments, and staff attrition. In response, this project was started to develop a comprehensive PAQ execution strategy to support the success of LANL’s manufacturing mission. This project’s method for developing an updated architecture was to create an integrated, flexible, reliable, and agile strategic process. The execution plan has five deliverables: 1) an integrated schedule view of PAQ work scope, 2) a resource management plan that aligns with the required scope, 3) a metrics monitoring dashboard, 4) a project management plan for sustaining NAP 401.1A implementation, and 5) a risk management plan. The research design is a mixed-method approach focused on data collection for each deliverable. The methodology entails qualitative and quantitative research, metrics monitoring, data analysis, and the creation of a dashboard. The qualitative methods used include literature reviews and interviews. The quantitative methods include resource, financial, schedule and survey data analysis. Preliminary and final results were peer reviewed by subject matter experts both within the ALDWP organization and deployed support.
This paper presents an independent component analysis (ICA) based unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC) load disaggregation using row-resolution (i.e., 15 minutes) smart meter data. We first demonstrate that the electricity consumption profiles on mild-temperature days can be used to approximate the base load on hot days. A residual load profile can then be calculated by subtracting the mild-day load profile from the hot-day load profile. The residual load profiles are processed using ICA for HVAC load extraction. An optimization-based algorithm is proposed for post-adjustment of the ICA results, considering two bounding factors for enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC energy bounds computed from the relationship between HVAC load and temperature to remove unrealistic HVAC load spikes. Second, we exploit the dependency between the daily nocturnal and diurnal loads extracted from historical meter data to smooth the base load profile. Pecan Street data with sub-metered HVAC data were used to test and verify the proposed methods. Simulation results demonstrated that the proposed method is computationally efficient and robust across multiple customers.
An analysis of data from epidemics makes it possible to determine their principal causes, governed by environmental factors (solar activity, etc.) The results of an analysis of the periodicity of the epidemic process in the case of diphtheria are presented which was conducted with the aid of autocorrelation and spectral methods of analysis. Numerical data (annual figures) are used on the dynamics of diphtheria in 50 regions (points) with a total duration of 2,777 years.
New analysis methods were developed and refined for the synthesis of wind fields from multiple Doppler radar data. Considerable software was written and debugged for wind field synthesis. The analysis methods were applied to radar data collected during the CCOPE experiment in which lidar wind measurements were also made. The analysis method differs from existing methods in that interpolation (using filters with assigned weights) and advection of data, to account for time differential between data acquisition at different points, are not used. Instead, functional fits were used in space and time coordinates to transfer radial velocity data to a space-time grid. Subsequently the wind synthesis is performed. This method gives better space resolution in the synthesized winds, compared to other methods in common use, by better preserving the gradients of velocities. The wind fields show the cellular structure characteristic of boundary-layer convection. Also evident in the analysis are the sharp transitions and gradients in the wind field which were preserved by the synthesis.
The availability of actinide standard materials for use in nuclear safeguard applications is critical, as is thorough characterization thereof. Although accurate trace element compositions and isotopic considerations are paramount for deployment of reference standards, structural characterization is also essential towards accurately describing the chemical form and potential matrix effects in candidate materials. Here, to this end, samples of NpO 2 were synthesized via a direct denitration (DD) method and probed with powder X-ray diffraction (PXRD), Raman spectroscopy, and scanning electron microscopy (SEM) for structural and morphological characterization and comparison with NpO 2 materials produced via modified direct denitration (MDD). PXRD confirmed the bulk identity of NpO 2 , and no additional phases were identified using this method. Analysis of Raman data collected using a 532 nm excitation wavelength indicates that samples are mostly phase pure; however, some variability in spectral features is observed. Analysis of additional spectroscopic data collected with a 785 nm excitation wavelength revealed variability in the relative intensity of spectral features. Raman spectroscopy indicates that the sample is primarily NpO 2 ; however, additional signals indicate possible structural disorder, oxidized species, or potential contributions from other Np phases. To further investigate the possibility of additional phase contributions within the sample of NpO 2 , Raman spectroscopic mapping was employed to examine the homogeneity of the sample produced via DD. From this analysis, we determined that despite variability in the intensity of Raman-active vibrational modes, consistent spectra are obtained throughout the area of the sample investigated. SEM images show aggregates with variable sizes and shapes, with rounded, primary particles possessing an average diameter of approximately 100 nm. Comparison of the results of these multimodal analyses to the literature indicates that the crystal chemical, spectroscopic, and microstructural properties of NpO 2 vary based on synthesis method, even if X-ray diffraction data indicate that the bulk phase is NpO 2 .
A second experimental Round Robin on the measurement of the crack opening load in fatigue crack growth tests has been completed by the ASTM Task Group E24.04.04 on Crack Closure Measurement and Analysis. Fourteen laboratories participated in the testing of aluminum alloy compact tension specimens. Opening-load measurements were made at three crack lengths during constant Delta K, constant stress ratio tests by most of the participants. Four participants made opening-load measurements during threshold tests. All opening-load measurements were based on the analysis of specimens compliance behavior, where the displacement/strain was measured either at the crack mouth or the mid-height back face location. The Round Robin data were analyzed for opening load using two non-subjective analysis methods: the compliance offset and the correlation coefficient methods. The scatter in the opening load results was significantly reduced when some of the results were excluded from the analysis population based on an accept/reject criterion for raw data quality. The compliance offset and correlation coefficient opening load analysis methods produced similar results for data populations that had been screened to eliminate poor quality data.
The National Aeronautics and Space Administration and the Chinese Aeronautical Establishment participated in a Fatigue and Fracture Mechanics Cooperative Program. The program objectives were to identify and characterize crack initiation and growth of small cracks (10 microns to 2 mm long) in commonly used US and PRC aluminum alloys, to improve fracture mechanics analyses of surface- and corner-crack configurations, and to develop improved life-prediction methods. Fatigue and small-crack tests were performed on single-edgenotch tension (SENT) specimens and large-crack tests were conducted on center-crack tension specimens for constant-amplitude (stress ratios of -1, 0, and 0.5) and Mini-TWIST spectrum loading. The plastic replica method was used to monitor the initiation and growth of small fatigue cracks at the semicircular notch. Crack growth results from each laboratory on 7075-T6 bare and LC9cs clad aluminum alloys agreed well and showed that fatigue life was mostly crack propagation from a material defect (inclusion particles or void) or from the cladding layer. Finite-element and weight-function methods were used to determine stress intensity factors for surface and corner cracks in the SENT specimens. Equations were then developed and used in a crack growth and crack-closure model to correlate small- and large-crack data and to make life predictions for various load histories. The cooperative program produced useful experimental data and efficient analysis methods for improving life predictions. The results should ultimately improve aircraft structural reliability and safety.
Liquid rocket engines using oxygen and methane propellants are being considered by the National Aeronautics and Space Administration (NASA) for in-space vehicles. This propellant combination has not been previously used in a flight-qualified engine system, so limited test data and analysis results are available at this stage of early development. NASA has funded several hardware-oriented activities with oxygen and methane propellants over the past several years with the Propulsion and Cryogenic Advanced Development (PCAD) project, under the Exploration Technology Development Program. As part of this effort, the NASA Marshall Space Flight Center has conducted combustion stability analyses of several of the configurations. This paper presents test data and analyses of combustion stability from the recent PCAD-funded test programs at the NASA MSFC. These test programs used swirl coaxial element injectors with liquid oxygen and liquid methane propellants. Oxygen was injected conventionally in the center of the coaxial element, and swirl was provided by tangential entry slots. Injectors with 28-element and 40-element patterns were tested with several configurations of combustion chambers, including ablative and calorimeter spool sections, and several configurations of fuel injection design. Low frequency combustion instability (chug) occurred with both injectors, and high-frequency combustion instability occurred at the first tangential (1T) transverse mode with the 40-element injector. In most tests, a transition between high-amplitude chug with gaseous methane flow and low-amplitude chug with liquid methane flow was readily observed. Chug analyses of both conditions were conducted using techniques from Wenzel and Szuch and from the Rocket Combustor Interactive Design and Analysis (ROCCID) code. The 1T mode instability occurred in several tests and was apparent by high-frequency pressure measurements as well as dramatic increases in calorimeter-measured heat flux throughout the chamber. Analyses of the transverse mode were conducted with ROCCID and empirical methods such as Hewitt d/V. This paper describes the test hardware configurations, test data, analysis methods, and presents results of the various analyses.
Observations from the last twenty years suggest the existence of electromagnetic (EM) phenomena during or preceding some earthquakes [Haykawa et a!, 2004; Pulinets at al, 1999,2004, 2006, Ouzounov et all 2007 and Liu et all 20041. Both our previous studies [Pulinets at al, 2005, 2006, Ouzounov et al, 2006, 20071 and the latest review by the Earthquake Remote Precursor Sensing panel [ERPS; 2003- 20051; have shown that there were precursory atmospheric TIR signals observed on the ground and in space associated with several recent earthquakes. [Tramutoli at al, 2005, 2006, Cervone et al, 2006, Ouzounov et all 2004,2006JT.o study these signals, we applied both multi parameter statistical analysis and data mining methods that require systematic measurements from an Integrated Sensor Web of observations of several physical and environmental parameters. These include long wave earth infra-red radiation, ionospheric electrical and magnetic parameters, temperature and humidity of the boundary layer, seismicity and may be associated with major earthquakes. Our goal is to verify the earthquake atmospheric correlation in two cases: (i) backward analysis - 2000-2008 hindcast monitoring of multi atmospheric parameters over the Kamchatka region, Russia ; and (ii) forward real-time alert analysis over different seismo-tectonic regions for California, Turkey, Taiwan and Japan. Our latest results, from several post-earthquake independent analyses of more then 100 major earthquakes, show that joint satellite and some ground measurements, using an integrated web, could provide a capability for observing pre-earthquake atmospheric signals by combining the information from multiple sensors into a common framework. Using our methodology, we evaluated and compared the observed signals preceding the latest M7.9 Sichuan earthquake (0511212008), M8.0 earthquake in Peru (0811512007), M7.6 Kashmir earthquake (1010812005) and M9.0 Sumatra earthquake (1212812004). We found evidence of the systematic appearance of both atmospheric and ionospheric anomalies preceding most of the major events during the period of our analysis 2001 -2008.
We explore the applications of machine learning techniques in relativistic laser-plasma experiments beyond optimization purposes. We predict the beam charge of electrons produced in a laser wakefield accelerator given the laser wavefront change caused by a deformable mirror. Machine learning enables feature analysis beyond merely searching for an optimal beam charge, showing that specific aberrations in the laser wavefront are favored in generating higher beam charges. Supervised learning models allow characterizing the measured data quality as well as recognizing irreproducible data and potential outliers. Furthermore, we also include virtual measurement errors in the experimental data to examine the model robustness under these conditions. This work demonstrates how machine learning methods can benefit data analysis and physics interpretation in a highly nonlinear problem of relativistic laser-plasma interaction.
Giovanni is the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure developed at NASA GES DISC which provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science data. It receives large number of user requests each day for a variety of analysis and visualization services, which leads to the big data challenge of serving gradually increasing large data volumes with diverse statistical algorithms. We hereby propose a multi-dimensional accumulation method which provides fast and cost-efficient cloud analysis for diverse services including both area averaging and time averaging. This method involves the weighted volume integration over multiple variable dimensions (time and space), and is implemented in AWS using Athena providing serverless and highly scalable data analysis. Compared to the standard method, this approach dramatically reduced the computational time by order of magnitude with a minimal AWS cost incurred. For example, for a benchmark of 10-year area averaging over the 1x1 degree daily variable, the computational time was reduced from minutes to seconds, and the Athena cost is only $5 for 100,000 requests.
Five basic problems or question areas are examined. They are as follows: (1) Evaluate adequacy of current problem/performance data base; (2) Evaluate methods of performing trend analysis; (3) Methods and sources of data for probabilistic risk assessment; and (4) How is risk assessment documentation upgraded and/or updated. The fifth problem was to provide recommendations for each of the above four areas.
The central theme of this review article is the role that dynamics plays in estimating the state of the atmosphere and of the ocean from incomplete and noisy data. Objective analysis and inverse methods represent an attempt at relying mostly on the data and minimizing the role of dynamics in the estimation. Four-dimensional data assimilation tries to balance properly the roles of dynamical and observational information. Sequential estimation is presented as the proper framework for understanding this balance, and the Kalman filter as the ideal, optimal procedure for data assimilation. The optimal filter computes forecast error covariances of a given atmospheric or oceanic model exactly, and hence data assimilation should be closely connected with predictability studies. This connection is described, and consequences drawn for currently active areas of the atmospheric and oceanic sciences, namely, mesoscale meteorology, medium and long-range forecasting, and upper-ocean dynamics.
We consider problem of nonlinear shrinkage of the metal part during bound metal deposition manufacturing on the ground and in zero-G. To analyze this problem we developed multi-scale physics-based approach that spans atomistic dynamics at the scale of nanoseconds and the full part shrinkage at the time scale of hours. Using this approach we estimated the key parameters of the problem including grain boundary width, coefficient of surface diffusion, initial redistribution of particles during debinding stage, micro-structure evolution from round particles to densely packed grains and corresponding change of the total and chemical free energy, and sintering stress. The introduced method was used to predict shrinkage at the level of two particles, filament cross-section, sub-model, and the whole green, brown, and metal parts. To further improve accuracy and reliability of the shrinkage predictions we propose concept of intelligent additive manufacturing of metal powders in space that combines the strengths of both physics-based and data-driven methods of analysis of AM.
The paper discusses the design, analysis, and test of hat stiffened panels subjected to a variety of thermal and mechanical load conditions. The panels were designed using data from structural optimization computer codes and finite element analysis. Test methods included the grid shadow moire method and a single gage force stiffness method. The agreement between the test data and analysis provides confidence in the methods that are currently being used to design structures for hypersonic vehicles. The agreement also indicates that post buckled strength may potentially be used to reduce the vehicle weight.
Probabilistic methods are presented for characterizing and quantifying uncertainties in models and model predictions. Techniques are given for constructing specific uncertainty distributions based on available information. Alternative techniques are given for propagating uncertainties in model inputs to obtain the uncertainty in the model result or prediction. Bayesian techniques are also described for utilizing data and information to update and revise model results and predictions. The focus is on applications with numerous specific examples given. The use of data to revise Micrometeoroid and Orbital Debris (MMOD) risk prediction models are among the examples given.