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DOE OSTI2020

Energy Intensity Baselining and Tracking Guidance

Each company joining the U.S. Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) commits to establishing an energy consumption and energy intensity (EI) baseline and to tracking its energy performance over a 10-year period against that baseline. The baseline must reflect a company’s energy consumption over a 12-month period, covering all its U.S.-based operations. Energy consumption is calculated by fuel type in terms of primary energy (also known as source energy). EI is broadly defined as the amount of energy consumed per unit of output produced. For this guidance document and for the program, the term energy performance represents an evaluation of a facility’s capacity to use energy efficiently. Metrics used to assess a facility’s energy performance can include EI, energy consumption, improvements in EI, etc. Establishing an energy baseline and tracking system is a critical first step in effectively managing energy use. Developing a baseline can help a company understand energy use within the corporation and give it a point of comparison to evaluate future efforts to improve energy performance. It can also support efforts to validate a company’s energy management activities, improve comparative analyses when using benchmarks, and help in predicting future energy needs. In addition, a company that normalizes its performance data can determine highly defensible measures of energy savings generated through implemented energy efficiency projects. Establishing a baseline and tracking energy performance is also a requirement for ISO 50001 certification. Although basic energy data can be collected through utility bills, most manufacturers will have to perform additional analyses to develop accurate and robust energy baselines and tracking systems. Energy is consumed in many ways within the manufacturing sector and can come from multiple sources. Energy is sometimes generated and sold to other parties or captured and reused on-site. External events can exert a significant impact on a facility or company’s energy use independent of any purposeful efforts to improve energy efficiency. Operational changes, such as production shifts—which may be inevitable for some companies over the 10-year period covered by the program—can also make a big difference in energy use. Since Better Plants asks companies to account for all their U.S.-based operations, mergers, acquisitions, and divestitures can also have significant implications for a company’s energy metrics. This document aims to demystify the sometimes complex baselining process. It devotes special attention to the task of normalizing and adjusting energy consumption to account for external factors, such as weather and production changes. A key recommendation is that companies use regression analysis to normalize their energy consumption data whenever possible. Regression analysis is a statistical technique that estimates the dependence of a variable (i.e., energy use in the context of Better Plants) on one or more independent variables such as ambient temperature, while controlling for the influence of other variables at the same time. A properly developed regression analysis can provide a reliable estimate of energy savings resulting from energy improvement strategies and projects by accounting for the effects of variables such as annual production levels and weather. DOE has developed a companion Energy Performance Indicator software tool (EnPI) to simplify the baselining process. This tool can run regression models, calculate changes in EI at the facility level, and automatically compile facility-level data into a corporate-wide metric. Note that although the relevant equations used to calculate EI are provided in this document, the EnPI tool will automatically perform most calculations for the user. Additionally, Better Plants Partners (Partners) can call on their Technical Account Manager (TAM) to help them establish a baseline and assist with the necessary calculations to track progress.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

Tracking Critical Thermal Metrics throughout the Life Cycle of a Large Observatory Thermal Model

Observatory thermal models for large, complex missions, such as the Wide Field InfraRed Survey Telescope (WFIRST) mission, produce an immense amount of data to be processed. Configuration management of the model throughout the project life cycle has mainly focused on which versions of the subsystem models form the current observatory level configuration. However, the results produced by the model are not nearly as well tracked and traceable. Given the various states of design maturity for each of the components in the WFIRST design, an updated component model is nearly ready to be integrated at the next higher level of assembly about every month or two. With each subsystem model delivery, the observatory model needs to remove the old component, integrate the new one, execute the model, and inspect the results. Usually, this inspection focuses primarily on the newly integrated component. Recently, a Metric Tracking Spreadsheet was developed to help provide a “big picture” view of the entire observatory highlighting key parameters critical to mission performance. This spreadsheet helps track impacts on subsystems by updates of other subsystems that were not intuitively obvious. Metrics tracked include: absorbed environmental loading (to determine effectiveness of sunshield), temperatures of critical avionics, electrical dissipations, heater power predictions, stability of critical optics, parasitic heat leaks in cryogenic region, high level heat flows between elements, and model run time. Producing this data for the same operational configuration with each model update has helped produce a trail of data to evaluate the impact of model updates. While the metrics selected are specific for WFIRST, other large, complex observatories could be well served to establish their own metrics early in the project life cycle to track to quickly assess the impact of any subsystem on other subsystems or the overall system itself.

Thermal Desktop↗

DOE OSTI2017

DES15E2mlf: A Spectroscopically Confirmed Superluminous Supernova that Exploded 3.5 Gyr After the Big Bang

We present the Dark Energy Survey (DES) discovery of DES15E2mlf, the most distant superluminous supernova (SLSN) spectroscopically con rmed to date. The light curves and Gemini spectroscopy of DES15E2mlf indicate that it is a Type I superluminous supernova (SLSN-I) at z = 1:861 (a lookback time of 10 Gyr) and peaking at MAB = -22:3 0:1 mag. Given the high redshift, our data probe the rest-frame ultraviolet (1400{3500 A) properties of the SN, nding velocity of the Ciii feature changes by 5600kms -1 over 14 days around maximum light. We nd the host galaxy of DES15E2mlf has a stellar mass of 3:5+3:6 -2:4 109 M , which is more massive than the typical SLSN-I host galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Data for Impact of Vertical and Seasonal Variation in Leaf Traits on Simulating Soybean Canopy Photosynthesis via 1D and 3D Modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax25), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax25 profile achieved comparable performance to the scheme with the measured Vcmax25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

Photosynthesis↗

DOE OSTI2026

Comparing ICME simulations with scaled laboratory experiment

In stellar physics and astrophysics, numerical simulations and laboratory experiments are often compared to observational data to support their representation of the real world. However, there is also merit in comparing numerical simulations to properly scaled experiments, especially when the experiment and the simulation are both emulating the solar phenomena. Confirming the credibility of scaled experiments and their scaling with well-validated models is important to expand our knowledge of the associated physical phenomena. This is significant because experiments and simulations can be performed frequently, whereas observations may be limited by location, field of view, and missing data. In this work, we use the Alfvén Wave Solar atmosphere Model, a well-validated magnetohydrodynamic model, to simulate an interplanetary coronal mass ejection (ICME) and compare it to an experiment which provides a scaled analog to a physical ICME. The experiment was performed on the Big Red Ball facility and scaled using dimensionless parameters such as plasma β and magnetosonic Mach number to reproduce the main structure of an ICME. We compare the model-simulated temperature, density, and magnetic field to those from the experiment, as well as the scaling parameters used in the experiment, to those calculated from the simulation. This comparison is performed to further justify the scaling arguments made by the experiment. Additionally, the comparison would lead to the development of stronger scaling arguments for future experiments.

Bryant, K. [University of Michigan, Ann Arbor, MI ↗

NASA NTRS2000

On-Line, Self-Learning, Predictive Tool for Determining Payload Thermal Response

This paper will present the results of a joint ManTech / Goddard R&D effort, currently under way, to develop and test a computer based, on-line, predictive simulation model for use by facility operators to predict the thermal response of a payload during thermal vacuum testing. Thermal response was identified as an area that could benefit from the algorithms developed by Dr. Jeri for complex computer simulations. Most thermal vacuum test setups are unique since no two payloads have the same thermal properties. This requires that the operators depend on their past experiences to conduct the test which requires time for them to learn how the payload responds while at the same time limiting any risk of exceeding hot or cold temperature limits. The predictive tool being developed is intended to be used with the new Thermal Vacuum Data System (TVDS) developed at Goddard for the Thermal Vacuum Test Operations group. This model can learn the thermal response of the payload by reading a few data points from the TVDS, accepting the payload's current temperature as the initial condition for prediction. The model can then be used as a predictive tool to estimate the future payload temperatures according to a predetermined shroud temperature profile. If the error of prediction is too big, the model can be asked to re-learn the new situation on-line in real-time and give a new prediction. Based on some preliminary tests, we feel this predictive model can forecast the payload temperature of the entire test cycle within 5 degrees Celsius after it has learned 3 times during the beginning of the test. The tool will allow the operator to play "what-if' experiments to decide what is his best shroud temperature set-point control strategy. This tool will save money by minimizing guess work and optimizing transitions as well as making the testing process safer and easier to conduct.

Jen, Chian-Li↗

DOE OSTI2017

Scaling Deep Learning on GPU and Knights Landing clusters

The speed of deep neural networks training has become a big bottleneck of deep learning research and development. For example, training GoogleNet by ImageNet dataset on one Nvidia K20 GPU needs 21 days. To speed up the training process, the current deep learning systems heavily rely on the hardware accelerators. However, these accelerators have limited on-chip memory compared with CPUs. To handle large datasets, they need to fetch data from either CPU memory or remote processors. We use both self-hosted Intel Knights Landing (KNL) clusters and multi-GPU clusters as our target platforms. From an algorithm aspect, current distributed machine learning systems are mainly designed for cloud systems. These methods are asynchronous because of the slow network and high fault-tolerance requirement on cloud systems. We focus on Elastic Averaging SGD (EASGD) to design algorithms for HPC clusters. Original EASGD used round-robin method for communication and updating. The communication is ordered by the machine rank ID, which is inefficient on HPC clusters. First, we redesign four efficient algorithms for HPC systems to improve EASGD's poor scaling on clusters. Async EASGD, Async MEASGD, and Hogwild EASGD are faster \textcolor{black}{than} their existing counterparts (Async SGD, Async MSGD, and Hogwild SGD, resp.) in all the comparisons. Finally, we design Sync EASGD, which ties for the best performance among all the methods while being deterministic. In addition to the algorithmic improvements, we use some system-algorithm codesign techniques to scale up the algorithms. By reducing the percentage of communication from 87% to 14%, our Sync EASGD achieves 5.3x speedup over original EASGD on the same platform. We get 91.5% weak scaling efficiency on 4253 KNL cores, which is higher than the state-of-the-art implementation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Doppler broadening in Mg 20 ( β p γ ) Ne 19 decay

The $^{15}$$\textbf{O}$$\Big({α,γ}\Big)$$^{19}$$\textbf{Ne}$ bottleneck reaction in Type I x-ray bursts is the most important thermonuclear reaction rate to constrain experimentally, to improve the accuracy of burst light-curve simulations. A proposed technique to determine the thermonuclear rate of this reaction employs the $^{20}$$\textbf{Mg}$$\Big({βpα}\Big)$$^{15}$$\textbf{O}$ decay sequence. The key $^{15}$$\textbf{O}$$\Big({α,γ}\Big)$$^{19}$$\textbf{Ne}$ resonance at an excitation of 4.03 MeV is now known to be fed in $^{20}$$\textbf{Mg}$$\Big({βpγ}\Big)$$^{19}$$\textbf{Ne}$ however, the energies of the protons feeding the 4.03 MeV state are unknown. Knowledge of the proton energies will facilitate future $^{20}$$\textbf{Mg}$$\Big({βpα}\Big)$$^{15}$$\textbf{O}$ measurements. To determine the energy of the proton transition feeding the 4.03 MeV state in $^{19}$$\textbf{Ne}$. A fast beam of $^{20}$$\textbf{Mg}$ was implanted into a plastic scintillator, which was used to detect $β$ particles. 16 high purity germanium detectors were used to detect $γ$ rays emitted following $βp$ decay. A Monte Carlo method was used to simulate the Doppler broadening of $^{19}$$\textbf{Ne}γ$-ray lines and compare to the experimental data. The center of mass energy between the proton and $^{19}$$\textbf{Ne}$, feeding the 4.03 MeV state, is measured to be $1.21^{+0.25}_{-0.22}$ $\textbf{MeV}$, corresponding to a $^{20}$$\textbf{Na}$ excitation energy of $7.44^{+0.25}_{-0.22}$$\textbf{MeV}$. Absolute feeding intensities and $γ$-decay branching ratios of $^{19}$$\textbf{Ne}$ states were determined including the 1615 keV state, which has not been observed before in this decay. A new $γ$ decay branch from the 1536 keV state in $^{19}$$\textbf{Ne}$ to the ground state is reported. The lifetime of the 1507 keV state in $^{19}$$\textbf{Ne}$ is measured to be $4.3^{+1.3}_{-1.1}$ ps resolving discrepancies in the literature. Conflicting $^{20}$$\textbf{Mg}$$\Big({βp}\Big)$ decay schemes in published literature are clarified.The utility of this Doppler broadening technique to provide information on $β$-delayed nucleon emission and excited-state lifetimes has been further demonstrated. In particular, knowledge of the proton energies feeding the 4.03 MeV $^{19}$$\textbf{Ne}$ state in $^{20}$$\textbf{Mg}$ $β$ decay will facilitate future measurements of the $α$-particle branching ratio.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1986

X-ray to infrared continua of optically selected quasars

X-ray-to-IR continuum data for nine optically selected (PG) quasars show a form which can be simply described in terms of two components - a power law of slope about 1 joining smoothly the 1-10-micron IR with the 0.1-10-keV X-ray points and (superimposed on this) a 'big bump' of optical-UV emission. The 'big bump' can be interpreted as thermal emission from an accretion disk. In a unique case where this 'big bump' extends to soft X-rays, the accretion disk parameters can be constrained interestingly.

Elvis, Martin↗

NASA NTRS2004

NASA GSFC's Role in the US Space Program

The paper discussss the GSFC research interests and how GSFC contributes to solve some of most basic questions Humans having been asking for thousands of years. How big is universe? How old is the universe? Will Humans and industrialization of the Earth change the climate significantly? Can Humans live in space? How does the Sun affect life on Earth? Goddard s role in Earth Science is very unique. We buy and build instruments that collect data about weather around the world. By flying those instruments on spacecraft, we have a unique vantage point to observe the weather patterns on a global scale. The best example is a satellite network called GOES (Geostationary Operational Environmental Satellite) which produces the weather pictures and videos you see on the nightly news and weather channel. Earth Science is another area of great interest to Goddard scientists and spacecraft designers. This photo of an oil fire in Iraq taken on March 2Ist of this year shows the down range effect pollution will have on entire region. Space Weather has become extremely important in the Space business. Satellites not only can become inoperable due to the occasional high level of radiation but astronauts can be exposed to dangerous levels of radiation. Space Weather is actually an issue when planning Extra Vehicular Activities (EVA). At Goddard, our operation of the Hubble Space Telescope has meant we have worked closely with several Shuttle crews over the years.

Simpson, James E.↗

NASA NTRS2024

Digital Lunar Exploration Sites (DLES) Terrain Crafting

Humans will soon be returning to the surface of the Moon with NASA’s Artemis program. The Artemis program is an international collaboration that will consist of a complex series of space systems and missions to explore the lunar surface and pave the way for the future exploration of Mars. NASA and its partners rely heavily on simulation for lighting and navigation studies as well as training astronauts, flight controllers, and mission support staff. The NASA Exploration Systems Simulations (NExSyS) team in the Simulation and Graphics Branch (ER7) in the Engineering Directorate at NASA’s Johnson Space Center has built up many simulation products to support this effort, one of which is the Digital Lunar Exploration Sites (DLES). DLES is a collection of products used to simulate and render the lunar surface in a digital environment. We discussed and presented an overview of the DLES products at the 2022 IEEE Aerospace Conference in Big Sky, MT with a paper titled "Digital Lunar Exploration Sites". This “DLES Terrain Crafting” paper will expand on the information previously provided in “DLES” paper and dive deeper into the details of the terrain crafting process and the toolsets used to support this task. The best digital data currently available of the lunar surface is provided by the Lunar Reconnaissance Orbiter (LRO). Its Lunar Orbiter Laser Altimeter (LOLA) achieves an impressive resolution of 5m per pixel at the Lunar South Pole (LSP) and can generate datasets covering a large continuous region near the LSP. There are a few additional methods, such as Shape from Shading which can infer higher resolution data (up to 1m per pixel) from the LRO Narrow Angle Camera (NAC) images. However, surface-based simulations require higher-resolution data, and this paper will discuss the process of enhancing the terrain to meet that need. The process begins with capturing statistical data of craters in the regions of interest using images provided by the LRO NAC. This data is then used to scatter artificial features which are not captured in the truth data, resulting in an enhanced DEM with a much higher resolution of 20cm per pixel. Many tools were built up to assist in the creation of these artificial Digital Elevation Models (DEM), which this paper will discuss in detail. DEMs themselves are a very powerful representation of a planetary surface, and many operations and tools can utilize the data they contain. This paper includes a description of the rendering of the lunar surface in a graphics engine, generation of contact patches to simulate tire to ground interaction, and ray tracing utilities to model Line of Sight (LOS) interactions with the terrain. This paper will also explore some new tool sets currently under development which aim to utilize Machine Learning (ML) to assist in the identification of craters from LRO NAC imagery. While this is not a novel idea, the NExSyS team is developing a unique approach which may result in more robust identification of crater characteristics.

Artemis↗

DOE OSTI2021

DNTTD (Distributed Non-Negative Tensor Train Decomposition)

The era of exascale computing opens new venues for innovations and discoveries in many scientific, engineering, and commercial fields. However, with the exa flops also come the extra-large high-dimensional data generated by high performance computing. High-dimensional data is presented as multidimensional arrays, aka tensors. The presence of latent (not directly observable) structures in the tensor allows a unique representation and compression of the data by classical tensor factorization techniques. However, the classical tensor methods are not always stable or they can be exponential in their memory requirements, which makes them not suitable for high-dimensional tensors. Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors. TT transforms the initial high-dimensional tensor in a network of three-dimensional tensors that requires only a linear storage. Many real-world data, such as, density, temperature, population, probability, etc., are non-negative and for an easy interpretation, the algorithms preserving non-negativity are preferred. Here, we introduce a distributed non-negative tensor-train and demonstrate its scalability and the compression on synthetic and real world big datasets.

Bhattarai, Manish↗

NASA NTRS2017

Planetesimals Born Big by Clustering Instability?

Roughly 100km diameter primitive bodies (today's asteroids and TNOs; [1]) are thought to be the end product of so-called "primary accretion". They dominated the initial mass function of planetesimals, and precipitated the onset of a subsequent stage, characterized by runaway gravitational effects, which proceeded onwards to planetary mass objects, some of which accreted massive gas envelopes. Asteroids are the parents of primitive meteorites; meteorite data suggest that asteroids initially formed directly from freelyfloating nebula particles in the mm-size range. Unfortunately, the process by which these primary 100km diameter planetesimals formed remains problematic. We review the most diagnostic primitive parent body observations, highlight critical aspects of the nebula context, and describe the issues facing various primary accretion models. We suggest a path forward that combines current scenarios of "turbulent concentration" (TC) and "streaming instabilities" (SI) into a triggered formation process we call clustering instability (CI). Under expected conditions of nebula turbulence, the success of these processes at forming terrestrial region (mostly silicate) planetesimals requires growth by sticking into aggregates in the several cm size range, at least, which is orders of magnitude more massive than allowed by current growth-by-sticking models using current experimental sticking parameters [2-4]. The situation is not as dire in the ice-rich outer solar system; however, growth outside of the snowline has important effects on growth inside of it [4] and at least one aspect of outer solar system planetesimals (high binary fraction) supports some kind of clustering instability.

Cuzzi, Jeffrey N.↗

NASA NTRS2017

Planetesimals Born Big by Clustering Instability?

Asteroids↗

DOE OSTI2025

AmeriFlux FLUXNET-1F US-xPU NEON Pu'u Maka'ala Natural Area Reserve (PUUM)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xPU NEON Pu'u Maka'ala Natural Area Reserve (PUUM). This is the FLUXNET version of the carbon flux data for the site US-xPU NEON Pu'u Maka'ala Natural Area Reserve (PUUM) produced by applying the standard ONEFlux (1F) software. Site Description - NEON's PUUM field site is located in the Pu'u Maka'ala Natural Area Reserve (NAR) on the eastern side of Hawaii’s “Big Island,” managed by the Hawaii Division of Forestry and Wildlife (DOFAW). More than 18,000 acres in size, the NAR is home to a rainforest with many native species, some of them endangered. It was established to protect some of the Big Island’s best wet native forest and unique geologic features.

Network), NEON (National Ecological Observatory [N↗

DOE OSTI2013

Proton form factor ratio, μ p G E P /G M P from double spin asymmetry

The form factors are fundamental properties of the nucleon representing the effect of its structure on its response to electromagnetic probes such as electrons. They are functions of the four-momentum transfer squared Q 2 between the electron and the proton. This thesis reports the results of a new measurement of the ratio of the electric and magnetic form factors of the proton up to Q 2 = 5.66 (GeV/c) 2 using the double spin asymmetry with a polarized beam and target. Experiment E07-003 (SANE, Spin Asymmetries of the Nucleon Experiment) was carried out in Hall C at Jefferson Lab in 2009 to study the proton spin structure functions with a dynamically polarized ammonia target and longitudinally polarized electron beam. By detecting elastically scattered protons in the High-Momentum Spectrometer (HMS) in coincidence with the electrons in the Big Electron Telescope Array (BETA), elastic measurements were carried out in parallel. The elastic double spin asymmetry allows one to extract the proton electric to magnetic form factor ratio G p E /G p M at high-momentum transfer, Q 2 = 5.66 (GeV/c) 2 . In addition to the coincidence data, inclusively scattered electrons from the polarized ammonia target were detected by HMS, which allows to measure the beam-target asymmetry in the elastic region with the target spin nearly perpendicular to the momentum transfer, and to extract G p E /G p M at low Q 2 = 2.06 (GeV/c) 2 . This alternative measurement of G p E /G p M has verified and confirmed the dramatic discrepancy at high Q 2 between the Rosenbluth and the recoil-polarization-transfer iv method with a different measurement technique and systematic uncertainties uncorrelated to those of the recoil-polarization measurements. The measurement of the form factor ratio at Q 2 = 2.06 (GeV/c) 2 has been determined as {mu}{sub p}G p E /G p M = 0.605{+-}0.178 stat {+-}0.033 sys which is in agreement with an earlier measurement with the polarized target technique at similar kinematics. The measurement of the form factor ratio at Q 2 = 5.66 (GeV/c) 2 has been determined as μ p G p E /G p M = 0.672 {+-} 0.362 stat which represents the highest Q 2 reach with the double spin asymmetry to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1974

The origin of the diffuse background gamma radiation

Recent observations provided evidence for diffuse background gamma radiation extending to energies beyond 100 MeV, and evidence of isotropy and implied cosmological origin. Significant features in the spectrum of this background radiation were observed which provide evidence for its origin in nuclear processes in the early stages of big-bang cosmology, and connect these processes with the galaxy formation theory. A test of the theory is in future observations of the background radiation in the 100 MeK to 100 GeV energy range which are made with large orbiting spark-chamber satellite detectors. The theoretical interpretations of present data, their connection with baryon-symmetric cosmology and galaxy formation theory, and the need for future observations are discussed.

Stecker, F. W.↗

NASA NTRS1993

RAID 7 disk array

Each RAID level reflects a different design architecture. Associated with each is a backdrop of imposed limitations, as well as possibilities which may be exploited within the architectural constraints of that level. There are three unique features that differentiate RAID 7 from all other levels. RAID 7 is asynchronous with respect to usage of I/O data paths. Each I/O drive (includes all data and one parity drives) as well as each host interface (there may be multiple host interfaces) has independent control and data paths. This means that each can be accessed completely, independently, of the other. This is facilitated by a separate device cache for each device/interface as well. RAID 7 is asynchronous with respect to device hierarchy and data bus utilization. Each drive and each interface is connected to a high speed data bus controlled by the embedded operating system to make independent transfers to and from central cache. RAID 7 is asynchronous with respect to the operation of an embedded real time process oriented operating system. This means that exclusive and independent of the host, or multiple host paths, the embedded OS manages all I/O transfers asynchronously across the data and parity drives. A key factor to consider is that of the RAID 7's ability to anticipate and match host I/O usage patterns. This yields the following benefits over RAID's built around micro-code based architectures. RAID 7 appears to the host as a normally connected Big Fast Disk (BFD). RAID 7 appears, from the perspective of the individual disk devices, to minimize the total number of accesses and optimize read/write transfer requests. RAID 7 smoothly integrates the random demands of independent users with the principles of spatial and temporal locality. This optimizes small, large, and time sequenced I/O requests which results in users having an I/O performance which approaches performance to that of main memory.

Stout, Lloyd↗