DSM analysis of support of disciplines in product development
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DNA affinity purification sequencing (DAP-seq) to identify putative transcriptional regulators of aromatic metabolism in Novosphingobium aromaticivorans
DNA affinity purification sequencing (DAP-seq) to identify putative transcriptional regulators of aromatic metabolism in Novosphingobium aromaticivorans
We study data traffic on distributed shared memory machines and conclude that data placement and grouping improve performance of scientific codes. We present several methods which user can employ to improve data traffic in his code. We report on implementation of a tool which detects the code fragments causing data congestions and advises user on improvements of data routing in these fragments. The capabilities of the tool include deduction of data alignment and affinity from the source code; detection of the code constructs having abnormally high cache or TLB misses; generation of data placement constructs. We demonstrate the capabilities of the tool on experiments with NAS parallel benchmarks and with a simple computational fluid dynamics application ARC3D.
This paper serves a twofold purpose: characterize the behavior of a reconfigurable chip exposed to radiation; and demonstrate a method for functionality recovery due to Total Ionizing Dose (TID) effects. The experiments are performed using a PL developed reconfigurable device, a Field Programmable Transistor Array (FPTA). The paper initially describes experiments on the characterization of the NMOS transistor behavior for TID values up to 300krad. The behavior of analog and digital circuits downloaded onto the FPTA chip is also assessed for TID effects. This paper also presents a novel approach for circuit functionality recovery due to radiation effects based on Evolvable Hardware. The key idea is to reconfigure a programmable device, in-situ, to compensate, or bypass its degraded or damaged components. Experiments with total radiation dose up to 300kRad show that while the functionality of a variety of circuits, including digital gates, a rectifier and a Digital to Analog Converter implemented on a FPTA-2 chip is degraded/lost at levels before 200kRad, the correct functionality can be recovered through the proposed evolutionary approach and the chips are able to survive higher radiation, for several functions in excess of total radiation dose of 250kRad.
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Increasing the efficiency and flexibility of electricity demand is necessary for ensuring a cost-effective and reliable transition to zero-carbon electricity systems. Such demand-side management (DSM) resources have been procured by utilities for decades via energy efficiency and demand response programs; however, the key drivers of program enrollment and customer participation levels remain poorly understood — even as governments and grid planners seek to scale up the deployment of DSM assets to meet climate targets. Here we systematically review the evidence on multiple factors that may influence customer enrollment and participation in building DSM programs, focusing primarily on residential and commercial buildings. We examine the contexts in which relationships between DSM factors and outcomes are most often explored and with which methods; we also score the strength, direction, and internal consistency of each factor's reported impact on the enrollment and participation outcomes. We find that studies most commonly assess the effects of economic incentives for load flexibility on program participation levels, often using simulation-based methods in lieu of measured data. Few studies focus on program enrollment outcomes or regulatory drivers of either enrollment or participation, and gaps are also evident in the coverage of emerging DSM opportunities like load electrification. Removal of structural barriers (e.g., the lack of controls infrastructure) and the use of third party services (e.g., load aggregators) are the factors with the largest positive impacts on DSM outcomes, but no single factor emerges as clearly most impactful. For a given factor, the range of reported impacts typically varies widely across the relevant studies reviewed. Our findings provide a snapshot of the state of knowledge about building DSM and customer decision-making, and they expose key gaps in understanding that must be filled if building DSM is to expand as a critical resource for operating clean power grids.
Satellite constellations present unique capabilities and opportunities to Earth orbiting and near-Earth scientific and communications missions, but also present new challenges to cost estimators. An effective and adaptive cost model is essential to successful mission design and implementation, and as Distributed Spacecraft Missions (DSM) become more common, cost estimating tools must become more representative of these types of designs. Existing cost models often focus on a single spacecraft and require extensive design knowledge to produce high fidelity estimates. Previous research has examined the shortcomings of existing cost practices as they pertain to the early stages of mission formulation, for both individual satellites and small satellite constellations. Recommendations have been made for how to improve the cost models for individual satellites one-at-a-time, but much of the complexity in constellation and DSM cost modeling arises from constellation systems level considerations that have not yet been examined. This paper constitutes a survey of the current state-of-the-art in cost estimating techniques with recommendations for improvements to increase the fidelity of future constellation cost estimates. To enable our investigation, we have developed a cost estimating tool for constellation missions. The development of this tool has revealed three high-priority weaknesses within existing parametric cost estimating capabilities as they pertain to DSM architectures: design iteration, integration and test, and mission operations. Within this paper we offer illustrative examples of these discrepancies and make preliminary recommendations for addressing them. DSM and satellite constellation missions are shifting the paradigm of space-based remote sensing, showing promise in the realms of Earth science, planetary observation, and various heliophysical applications. To fully reap the benefits of DSM technology, accurate and relevant cost estimating capabilities must exist; this paper offers insights critical to the future development and implementation of DSM cost estimating tools.
Satellite constellations present unique capabilities and opportunities to Earth orbiting and near-Earth scientific and communications missions, but also present new challenges to cost estimators. An effective and adaptive cost model is essential to successful mission design and implementation, and as Distributed Spacecraft Missions (DSM) become more common, cost estimating tools must become more representative of these types of designs. Existing cost models often focus on a single spacecraft and require extensive design knowledge to produce high fidelity estimates. Previous research has examined the limitations of existing cost practices as they pertain to the early stages of mission formulation, for both individual satellites and small satellite constellations. Recommendations have been made for how to improve the cost models for individual satellites one-at-a-time, but much of the complexity in constellation and DSM cost modeling arises from constellation systems level considerations that have not yet been examined. This paper constitutes a survey of the current state-of-theart in cost estimating techniques with recommendations for improvements to increase the fidelity of future constellation cost estimates. To enable our investigation, we have developed a cost estimating tool for constellation missions. The development of this tool has revealed three high-priority shortcomings within existing parametric cost estimating capabilities as they pertain to DSM architectures: design iteration, integration and test, and mission operations. Within this paper we offer illustrative examples of these discrepancies and make preliminary recommendations for addressing them. DSM and satellite constellation missions are shifting the paradigm of space-based remote sensing, showing promise in the realms of Earth science, planetary observation, and various heliophysical applications. To fully reap the benefits of DSM technology, accurate and relevant cost estimating capabilities must exist; this paper offers insights critical to the future development and implementation of DSM cost estimating tools.
Stereogrammetry applied to globally available high resolution spaceborne imagery (HRSI; less than 5 m spatial resolution) yields fine-scaled digital surface models (DSMs) of elevation. These DSMs may represent elevations that range from the ground to the vegetation canopy surface, are produced from stereoscopic image pairs (stereo pairs) that have a variety of acquisition characteristics, and have been coupled with lidar data of forest structure and ground surface elevation to examine forest height. This work explores surface elevations from HRSI DSMs derived from two types of acquisitions in open canopy forests. We (1) apply an automated mass-production stereogrammetry workflow to along-track HRSI stereo pairs, (2) identify multiple spatially coincident DSMs whose stereo pairs were acquired under different solar geometry, (3) vertically co-register these DSMs using coincident spaceborne lidar footprints (from ICESat-GLAS) as reference, and(4) examine differences in surface elevations between the reference lidar and the co-registered HRSI DSMs associated with two general types of acquisitions (DSM types) from different sun elevation angles. We find that these DSM types, distinguished by sun elevation angle at the time of stereo pair acquisition, are associated with different surface elevations estimated from automated stereogrammetry in open canopy forests. For DSM values with corresponding reference ground surface elevation from spaceborne lidar footprints in open canopy northern Siberian Larix forests with slopes less than10, our results show that HRSI DSM acquired with sun elevation angles greater than 35deg and less than 25deg (during snow-free conditions) produced characteristic and consistently distinct distributions of elevation differences from reference lidar. The former include DSMs of near-ground surfaces with root mean square errors less than 0.68 m relative to lidar. The latter, particularly those with angles less than 10deg, show distributions with larger differences from lidar that are associated with open canopy forests whose vegetation surface elevations are captured. Terrain aspect did not have a strong effect on the distribution of vegetation surfaces. Using the two DSM types together, the distribution of DSM-differenced heights in forests (6.0 m, sigma = 1.4 m) was consistent with the distribution of plot-level mean tree heights (6.5m, sigma = 1.2 m). We conclude that the variation in sun elevation angle at time of stereo pair acquisition can create illumination conditions conducive for capturing elevations of surfaces either near the ground or associated with vegetation canopy. Knowledge of HRSI acquisition solar geometry and snow cover can be used to understand and combine stereogrammetric surface elevation estimates to co-register rand difference overlapping DSMs, providing a means to map forest height at fine scales, resolving the vertical structure of groups of trees from spaceborne platforms in open canopy forests.
In this paper, turbulence-closure models are evaluated using the 'true' LES approach in turbulent channel flow. The study is an extension of the work presented by Gullbrand (2001), where fourth-order commutative filter functions are applied in three dimensions in a fourth-order finite-difference code. The true LES solution is the grid-independent solution to the filtered governing equations. The solution is obtained by keeping the filter width constant while the computational grid is refined. As the grid is refined, the solution converges towards the true LES solution. The true LES solution will depend on the filter width used, but will be independent of the grid resolution. In traditional LES, because the filter is implicit and directly connected to the grid spacing, the solution converges towards a direct numerical simulation (DNS) as the grid is refined, and not towards the solution of the filtered Navier-Stokes equations. The effect of turbulence-closure models is therefore difficult to determine in traditional LES because, as the grid is refined, more turbulence length scales are resolved and less influence from the models is expected. In contrast, in the true LES formulation, the explicit filter eliminates all scales that are smaller than the filter cutoff, regardless of the grid resolution. This ensures that the resolved length-scales do not vary as the grid resolution is changed. In true LES, the cell size must be smaller than or equal to the cutoff length scale of the filter function. The turbulence-closure models investigated are the dynamic Smagorinsky model (DSM), the dynamic mixed model (DMM), and the dynamic reconstruction model (DRM). These turbulence models were previously studied using two-dimensional explicit filtering in turbulent channel flow by Gullbrand & Chow (2002). The DSM by Germano et al. (1991) is used as the USFS model in all the simulations. This enables evaluation of different reconstruction models for the RSFS stresses. The DMM consists of the scale-similarity model (SSM) by Bardina et al. (1983), which is an RSFS model, in linear combination with the DSM. In the DRM, the RSFS stresses are modeled by using an estimate of the unfiltered velocity in the unclosed term, while the USFS stresses are modeled by the DSM. The DSM and the DMM are two commonly used turbulence-closure models, while the DRM is a more recent model.
Distributed shared memory (DSM) implemented on a cluster of workstations is an increasingly attractive platform for executing parallel scientific applications. Checkpointing and rollback techniques can be used in such a system to allow the computation to progress in spite of the temporary failure of one or more processing nodes. This paper presents the design of an independent checkpointing method for DSM that takes advantage of DSM's specific properties to reduce error-free and rollback overhead. The scheme reduces the dependencies that need to be considered for correct rollback to those resulting from transfers of pages. Furthermore, in-transit messages can be recovered without the use of logging. We extend the scheme to a DSM implementation using lazy release consistency, where the frequency of dependencies is further reduced.
Opportunities for multi-point measurements, greater revisit frequency, failure robustness, and improved cost effectiveness motivate consideration of Distributed Spacecraft Missions (DSMs) for future Earth science missions. However, careful analysis is required to assess the distributed sensing capabilities of a constellation compared to more mature monolithic spacecraft while also considering other important dimensions such as cost and risk. The large combinatorial DSM design space limits existing mission analysis tools and exploration methods which emphasize monolithic design variables. The Trade-space Analysis Tool for Constellations (TAT-C) under development at Goddard seeks to enumerate and evaluate alternative mission architectures to minimize cost and maximize scientific return for pre-defined goals during pre-phase A analysis.Similar to other model-centric engineering efforts, efficient data management is a significant challenge for DSM mission analysis. In TAT-C, a Knowledge Base (KB) is envisioned as a cumulative central repository of information and meta-information about DSMs. Initial KB concepts store related data for reuse within or across mission analyses; however, over time, the KB is envisioned to be an important layer to coordinate actions of both human analysts and automated design agents to search a large design space for desirable mission alternatives. Preliminary KB research builds on a modern web technology stack to provide the following functionality: 1) storage of trade-space search requests which set requirements and constraints for DSM concepts, 2) storage of analysis results which quantify performance metrics for evaluated DSM concepts, 3) a RESTful application programming interface (API) for scripted access to data from TAT-C modules, 4) web-based graphical user interface (GUI) for manual access to underlying data, and 5) access control and management restrictions relevant to data protection and security. These efforts have culminated in a prototype KB used by the research team during TAT-C development to assess opportunities for future work.
The Shaped Pupil Coronagraph (SPC) is one of the two operating modes of the baseline coronagraph instrument for the proposed WFIRST mission. While in SPC mode, multiple sets of shaped pupil masks and focal plane masks would be available for various imaging tasks. The disk science mask set (SPC-DSM) is designed for exozodiacal disk science. With a 360 degree high contrast field of view, extending up to 20 λ/D, the SPC-DSM provides a powerful tool to study exozodiacal dust clouds associated with stellar debris disks to gain insight of the exoplanet formation and stellar disk dynamics. We will describe the performance verification and demonstration of the SPC-DSM coronagraph as tested in the high contrast imaging testbed (HCIT) at JPL. The goal of the testbed demonstration is an average contrast of 5e-9 over a 10% bandwidth centered at 565nm, in a field of view extending from 6.5 λ/D to 20 λ/D. We will discuss electric field conjugation, performance metrics, and model agreement as applied to the SPC-DSM.
This code compares the runtimes between the Dirichlet Dempster-Shafer Model (DSM) against the competition method, the Simplex DSM. Besides the code used to implement the Dirichlet DSM, all code to be released implements existing methods that are not novel algorithms nor any major innovations to existing software.
A numerical and experimental study of a confined strong swirling flow is presented. Detailed velocity measurements are made using a two-component laser Doppler velocimeter (LDV) technique. Computations are performed using a differential second-moment (DSM) closure. The effect of inlet dissipation rate on calculated mean and turbulence fields is investigated. Various model constants are employed in the pressure-strain model to demonstrate their influences on the predicted results. Finally, comparison of the DSM calculations with the algebraic second-monent (ASM) closure results shows that the DSM is better suited for complex swirling flow analysis.
Information is given in viewgraph form for turbulence modeling in computational fluid dynamics (CFD). The Eddy Viscosity Models (EVM), Algebraic Second Moment Closures (ASM), and Differential Second-Moment Closures (DSM) are considered. It is concluded that EVM's, ASM's, and DSM's will remain in use, though with a steady decline in importance of EVM's and ASM's in favor of DSM's. Improved versions of low-Re two-equation EVM's should lead to more reliable predictions of separated flows than are achievable at present. Further refinement of sub-models in second moment closures can be expected throughout this decade. There will be increasing attention given to interfacing SMC with higher order approaches such as LES, and an increased use of two-time-scale schemes providing distinct time scales for large and fairly small eddies.