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MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-service
Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides the agility required to meet our customers' increasing and changing needs. Cloud Computing is providing a new tier in the data services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. For climate science, Cloud Computing's capacity to engage communities in the construction of new capabilies is perhaps the most important link between Cloud Computing and Big Data.
Analytical Expression for DC Link Capacitor Current in a Cascaded H-Bridge Multi-Level Active Front-End Converter
Medium-voltage grid-tied systems often use a cascaded H-bridge multi-level active front-end. In this converter, dc link bus capacitors play an important role in stabilizing the converter and enabling both active and reactive power injections. The present work provides analytical expressions for the capacitor current, which are essential for optimizing system design (especially capacitor size vs. lifetime). Then, the expression is incorporated into the grid connected bidirectional power system model. Consequently, this work contributes to the guiding principles to choose accurate dc link capacitor ratings against grid-side power delivery requirements. The analytical results have been validated with detailed simulations and hardware results.
Design sensitivity derivatives for isoparametric elements by analytical and semi-analytical approaches
This paper presents an analytical approach for incorporating design sensitivity calculations directly into the finite element analysis. The formulation depends on the implicit differentiation approach and requires few additional calculations to obtain the design sensitivity derivatives. In order to evaluate this approach, it is compared with the semi-analytical approach which is based on commonly used finite difference formulations. Both approaches are implemented to calculate the design sensitivities for continuum and structural isoparametric elements. To demonstrate the accuracy and robustness of the developed analytical approach compared to the semi-analytical approach, some test cases using different structural and continuum element types are presented.
Experimental and analytical study of the longitudinal aerodynamic characteristics of analytically and empirically designed Strake-wing configurations at subcritical speeds
Sixteen analytically and empirically designed strakes have been tested experimentally on a wing-body at three subcritical speeds in such a way as to isolate the strake-forebody loads from the wing-afterbody loads. Analytical estimates for these longitudinal results are made using the suction analogy and the augmented vortex lift concepts. The synergistic data are reasonably well estimated or bracketed by the high- and low-angle-of-attack vortex lift theories over the Mach number range and up to maximum lift or strake-vortex breakdown over the wing. Also, the strake geometry is very important in the maximum lift value generated and the lift efficiency of a given additional area. Increasing size and slenderness ratios are important is generating lift efficiently, but similar efficiency can also be achieved by designing a strake with approximately half the area of the largest gothic strake tested. These results correlate well with strake-vortex-breakdown observations in the water tunnel.
Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations
Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve efficiency and throughput. Because of the complexity and scale of systems and workflows and the need for low-latency response to address dynamic circumstances, automated feedback and response have the potential to be more effective than current human-in-the-loop approaches which are laborious and error prone. Progress has been limited, however, by factors such as the lack of infrastructure and feedback hooks, and successful deployment is often site- and case-specific. In this position paper we report on the outcomes and plans from a recent Dagstuhl Seminar, seeking to carve a path for community progress in the development of autonomous feedback loops for MODA, based on the established formalism of similar (MAPE-K) loops in autonomous computing and self-adaptive systems. By defining and developing such loops for significant cases experienced across HPC sites, we seek to extract commonalities and develop conventions that will facilitate interoperability and interchangeability with system hardware, software, and applications across different sites, and will motivate vendors and others to provide telemetry interfaces and feedback hooks to enable community development and pervasive deployment of MODA autonomy loops.
LLNL ES&H Analytical Services and Instrumentation Analytical Laboratory (ALAB) (CY2022 Management Review Report)
"An annual review shall be conducted of the analytical activities to ensure continuing suitability, adequacy, and effectiveness." (ALAB-01 Rev 6 ALQAP section 6.11.2) "The laboratory management shall review its management system at planned intervals, in order to ensure its continuing suitability, adequacy and effectiveness..."(ISO/IEC 17025:2017 Section 8.9.1) "In accordance with a predetermined schedule and procedure, the laboratory's top management shall periodically conduct a review of the laboratory's management system and testing and/or calibration activities to ensure their continuing suitability and effectiveness, and to introduce necessary changes or improvements. "(TNI Standard EL-V1M2-2016-Rev2.1:Quality Systems General Requirements)
Improved analytic longitudinal response analysis for axisymmetric launch vehicles. Volume I - Linear analytic model
Improved analytic longitudinal response analysis for axisymmetric launch vehicles - linear model
Analytical investigation of turbine erosion phenomena. Volume I - Assembly of analytical model of wet vapor turbine blade erosion Interim technical report
Construction and application of analytical model of wet vapor turbine blad erosion
Increasing accessibility to deep learning-based analytics for space biology: pretrained models, transfer learning, and analytics platform development
Biological systems react in complex ways to the stressors of spaceflight, and the data capturing these relationships is concomitantly high-dimensional and complex. Deep learning and machine learning approaches are increasingly popular as an analytical approach for space biosciences, due to their ability to model complex relationships in complex data. However, such approaches often require large datasets and extensive computational resources. New approaches that minimize data sizes and computational power needed to leverage machine learning, and resources that make these approaches accessible, are needed to increase accessibility and adoption of machine learning in the space biosciences. Transfer learning, in which a pretrained model of broad utility is trained on a large dataset, and subsequently reused on downstream applications for which data is more limited, is one approach to minimizing data and computational intensity of deep learning applications. This transfer learning approach results in more performant models in high-dimensional, low-sample-size settings such as space biology, as compared to training models on limited data from scratch. This presentation will outline efforts to generate pretrained models for the space biology community, and highlight transfer learning applications modeling microbial antibiotic resistance during spaceflight. Finally, in order to increase accessibility of these models and tools, as well as others, for the broader space biology community, we present a modeling and analysis platform facilitating machine learning applications in space biology. This platform streamlines machine learning training and analysis in a notebook format, facilitates download and use of space biology data from the NASA GeneLab database, and can be utilized on NASA-hosted servers or downloaded and hosted locally. This effort, as part of the AI4LS (Artificial Intelligence for Life in Space) working group, will increase accessibility, feasibility, and performance of machine learning approaches for the space biology community.
Determination of Biogenic Content by 14 C in fuels using Liquid Scintillation Analysis Laboratory Analytical Procedure (Laboratory Analytical Procedure)
This procedure covers the determination of the percent 14 C in biogenic gasoline, jet fuel, and diesel range hydrocarbons prepared from distillation of hydrotreated pyrolysis oils and blended with fossil derived hydrocarbons (e.g. fossil diesel, gasoline, jet, or toluene). Either an internal 14C standard or a color quench curve is used to correct for potential signal quenching effects. Recent publications provide some background of direct LSC methods used for determination of biogenic fuel content.
The Area Localized Coupled Model for Analytical Mean Flow Prediction in Arbitrary Wind Farm Geometries
This work introduces the area localized coupled (ALC) model, which extends the applicability of approaches that couple classical wake superposition models and atmospheric boundary layer models to wind farms with arbitrary layouts. Coupling wake and top–down boundary layer models is particularly challenging since the latter requires averaging over planform areas associated with turbine-specific regions of the flow that need to be specified. The ALC model uses Voronoi tessellation to define this local area around each turbine. A top–down description of a developing internal boundary layer is then applied over Voronoi cells upstream of each turbine to estimate the local mean velocity profile. Coupling between the velocity at hub-height based on this localized top–down model and a wake model is achieved by enforcing a minimum least-square-error in mean velocity in each cell. The wake model in the present implementation takes into account variations in wind farm inflow velocity and represents the wake profile behind each turbine as a super-Gaussian function that smoothly transitions between a top-hat shape in the region immediately following the turbine to a Gaussian profile downstream. Detailed comparisons to large-eddy simulation (LES) data from two different wind farms demonstrate the efficacy of the model in accurately predicting both wind farm power output and local turbine hub-height velocity for different wind farm geometries. These validations using data generated from two different LES codes demonstrate the model's versatility with respect to capturing results from different simulation setups and wind farm configurations.
Noncircular orifice holes and advanced fabrication techniques for liquid rocket injectors. Phase 3: Analytical and cold-flow experimental evaluation of rectangular concentric tube injector elements for gas/liquid application. Phase 4: Analytical and experimental evaluation of noncircular injector elements for gas/liquid and liquid/liquid application
Results are presented of a cold-flow and hot-fire experimental study of the mixing and atomization characteristics of injector elements incorporating noncircular orifices. Both liquid/liquid and gas/liquid element types are discussed. Unlike doublet and triplet elements (circular orifices only) were investigated for the liquid/liquid case while concentric tube elements were investigated for the gas/liquid case. It is concluded that noncircular shape can be employed to significant advantage in injector design for liquid rocket engines.
Analytical study of the inside-out Gimbal dynamics. Volume 1: Analytical study of inside-out/coincident Gimbal dynamics
The performance capabilities and limitations of the instrument pointing system (IPS) are described. Suggestions of design modifications that result in overall improved IPS performance are included. Since the design and configuration of the IPS was modified a portion of the study was performed with the inside-out Gimbal configuration which was updated to the present coincident Gimbal system configuration. Due to the similarity of the two systems, the results obtained for the inside-out Gimbal also apply to the coincident Gimbal system.
Analytical prediction of the interior noise for cylindrical models of aircraft fuselages for prescribed exterior noise fields. Phase 1: Development and validation of preliminary analytical models
The basic theoretical work required to understand sound transmission into an enclosed space (that is, one closed by the transmitting structure) is developed for random pressure fields and for harmonic (tonal) excitation. The analysis is used to predict the noise reducton of unpressurized unstiffened cylinder, and also the interior response of the cylinder given a tonal (plane wave) excitation. Predictions and measurements are compared and the transmission is analyzed. In addition, results for tonal (harmonic) mechanical excitation are considered.
An analytical evaluation of mascon effects in a semi-analytic theory
A semianalytic method to predict the orbit of a spacecraft orbiting a planet and perturbed by oblateness and a gravity anomaly (mascon) is presented. The Hamiltonian is first expressed in closed form in terms of the nonsingular canonical set of Poincare elements where the mascon is represented by a point-mass. The planet global potential is limited to the second and third harmonics. The mascon potential in harmonics is limited to second degree and first order. The original Lie-Hori method is then applied to transform the canonical equations of motion from the osculating element space to the mean element space. Numerical integration of the new equations is used.