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Presentation on a Space Acceleration Measurement System (SAMS)
The primary objective of the Space Acceleration Measurement Systems (SAMS) project is to provide an acceleration measurement system capable of serving a wide variety of space experiments. The design of the system being developed under this project takes into consideration requirements for experiments located in the middeck, in the orbiter bay, and in Spacelab. In addition to measuring, conditioning, and recording accelerations, the system will be capable of performing complex calculations and interactive control. The main components consist of a remote triaxial optical storage device. In operation, the triaxial sensor head produces output signals in response to acceleration inputs. These signals are preamplified, filtered and converted into digital data which is then transferred to optical memory. The system design is modular, facilitating both software and hardware upgrading as technology advances. Two complete acceleration measurement flight systems will be build and tested under this project.
Toward a Seamless Integration of Computing, Experimental, and Observational Science Facilities: A Blueprint to Accelerate Discovery
The Department of Energy, Office of Science operates world-leading facilities for experimental, observational, and computational science. DOE supercomputing facilities will reach performance at the scale of ExaFLOPs in the coming years, enabling new vistas of scale and precision for large scale simulations and data analysis. Experimental scientific facilities are undergoing similar upgrades that will lead to higher data rates and correspondingly larger computational demands, and will increase the need for near-real-time processing and resilient support for more complex workflows. A transformation of science is underway, with workloads at supercomputing facilities increasingly driven by this explosion of data from instruments and experimental facilities, as well as the accelerating use of Artificial Intelligence (AI) as a tool for scientific discovery. A seamless integration of computing, networking, instruments, and experimental facilities is required to support these emerging workloads and open up a new frontier of U.S. leadership in scientific discovery. We propose to accomplish this by providing frictionless access to the ASCR supercomputing facilities. We describe our vision of combining the power of ASCR supercomputers and networking infrastructure into an integrated scalable fabric, available to end user scientists via interfaces that aim to automate and simplify access to high performance computing systems. This will enable unprecedented computational science capabilities for experimental and observational facilities, and will create new opportunities to combine large simulations and modeling with experimental facility data analysis. This blueprint for creating an integrated network of computational and experimental facilities will provide an enriched discovery environment and open doors for new scientific communities to access the DOE’s world-leading computing and networking capabilities.
Alabama Carbon Storage: Bringing Data to the People
The Gulf Coastal Plain of Alabama has proven potential for geologic carbon storage and current interest in the area for large carbon capture and storage (CCS) projects is high. Extensive CCS relevant data exist in the records of the Geological Survey of Alabama and State Oil and Gas Board of Alabama, however, most of this data is not publicly available or is scattered in separate databases, file cabinets, and tables in publications. The “Alabama Carbon Storage: Data Sharing and Engagement” (ACS-DSE) project seeks to accelerate the responsible development of large CCS projects in the Gulf Coastal Plain of Alabama and offshore in state waters through a publicly accessible database of geologic carbon storage models and data across the region. The ACS-DSE draws on the over 150 years of geologic research and over 20 years of experience in CCS research to place relevant geologic, geophysical, and infrastructure data on a single web platform. Datasets available will include formation depths and elevations, geologic structures, reservoir properties, digital well logs (LAS files), existing penetrations, and geologic models. In addition to downloadable datasets, links to CCS related regulatory agencies and other sources of information will be included (for example, Class VI UIC permitting regulations and pipeline regulations). By making these datasets and models available in commonly used formats on a public website, the project will increase transparency in decision making and decrease the data acquisition time for industry.
Prototype hardware design and testing of the global common module for the global trigger subsystem of the ATLAS phase-II upgrade
We report the High-Luminosity Large Hadron Collider (HL-LHC) will deliver more than ten times the integrated luminosity of the previous runs combined. Meeting its stricter throughput requirements poses new challenges to the Trigger and Data Acquisition (TDAQ) systems of the LHC experiments. Introduced in the framework of the ATLAS experiment’s HL upgrade, the Global Trigger (GT) is a new subsystem which will perform offline-like algorithms on full-granularity calorimeter data. The implementation of the GT’s functionality is firmware-focused and is composed of three layers: multiplexing (or data aggregating), global event processing, and demultiplexing interface to the central trigger processor. Each layer will be composed of several, similar nodes, hosted on replicas of identical hardware, the Global Common Module (GCM), an ATCA front board which is designed to be adopted throughout the entire GT subsystem. This article proceeds from the TWEPP 2021 conference and presents the GCM hardware design, performed in 2020, and focuses on some key results of its extensive testing performed in 2021.
Gamma-ray lines from the Orion complex
We show that the 4.44 and 6.13 MeV line emission observed with the Compton Telescope (COMPTEL) from Orion is consistent with gamma-ray spectra consisting of a mixture of narrow and broad lines or spectra containing only broad lines. We employed several accelerated particle compositions and showed that the current COMPTEL data in the 3-7 MeV region alone cannot distinguish between the various possibilities. However, the COMPTEL upper limits in the 1-3 MeV band favor a composition similar to that of the winds of Wolf-Rayet stars of spectral type WC. The power dissipated by the accelerated particles at Orion is about 4 x 10(exp 38) ergs/s. These particles are not expected to produce significant amounts of Al-26.
Integrating Energy-Efficient Computing with Computational Research to Accelerate Energy Technology
NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient data centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.
The acceleration and propagation of solar flare energetic particles
A review of the most pertinent data on solar energetic particles is presented, and the implications of the data are discussed, taking into account radio emissions, hard X-rays, gamma rays, energy spectra and electron-proton correlations, chemical compositions, and isotopic and ionic compositions. The mechanisms of solar flare particle acceleration are considered along with solar flare particle spectra in interplanetary space. Attention is given to stochastic acceleration, shock acceleration, acceleration in direct electric fields, the mean free paths of solar electrons and protons in interplanetary space, and an illustration of the probable effect of adiabatic deceleration on the spectra of solar flare ions at the time of maximum.
Comment on 'Magnetospheric origin of energetic (E greater than or equal to 50 keV) ions upstream of the bow shock: The October 31, 1977, event' by G. C. Anagnostopoulos, E. T. Sarris, and S. M. Krimigis
Observational data on the effects of the solar burst event of October 31, 1977 on the earth bow shock are reassessed in a critical examination of the hypothesis of Anagnostopoulos et al. (1986), that energetic ions detected upstream of the shock originated in the magnetosphere and then leaked into the upstream region. The upstream and magnetospheric observations are compared, and consideration is given to the proton energy spectrum, anisotropies, and connection time. It is found that the event in question can best be explained in terms of Fermi shock acceleration. In a reply by Anagnostopoulos et al., additional data on this and similar events are presented in extensive graphs and analyzed. It is argued that there are many observed phenomena which cannot be explained by Fermi acceleration but are consistent with upstream leakage.
Trajectory Reconstruction of the ST-9 Sounding Rocket Experiment Using IMU and Landmark Data
This paper presents trajectory reconstruction of the ST-9 sounding rocket experiment using the onboard IMU data and descent imagery. The raw IMU accelerometer measurements are first converted into inertial acceleration and then used in trajectory integration. The descent images are pre-processed using a map-matching algorithm and unique landmarks for each image are created. Using the converted IMU data and descent images, the result from dead-reckoning and the kinematic-fix approaches are first compared with the GPS measurements. Then, both the IMU data and landmarks are processed together using a batch least-squares filter and the position, velocity, stochastic acceleration, and camera orientation of each image are estimated. The reconstructed trajectory is compared with the GPS data and the corresponding formal uncertainties are presented. The result shows that IMU data and descent images processed with a batch filter algorithm provide the trajectory accuracy required for pin-point landing.
Graph learning for particle accelerator operations
Particle accelerators play a crucial role in scientific research, enabling the study of fundamental physics and materials science, as well as having important medical applications. This study proposes a novel graph learning approach to classify operational beamline configurations as good or bad. By considering the relationships among beamline elements, we transform data from components into a heterogeneous graph. We propose to learn from historical, unlabeled data via our self-supervised training strategy along with fine-tuning on a smaller, labeled dataset. Additionally, we extract a low-dimensional representation from each configuration that can be visualized in two dimensions. Leveraging our ability for classification, we map out regions of the low-dimensional latent space characterized by good and bad configurations, which in turn can provide valuable feedback to operators. This research demonstrates a paradigm shift in how complex, many-dimensional data from beamlines can be analyzed and leveraged for accelerator operations.
Final shuttle-derived atmospheric database: Development and results from thirty-two flights
The final Shuttle-derived atmospheric data base is presented. The relational data base is comprised of data from 32 Space Transportation System (STS) descent flights, to include available meteorology data taken in support of each flight. For the most part, the available data are restricted to the middle atmosphere. In situ accelerations, sensed by the tri-redundant Inertial Measurement Unit (IMU) to an accuracy better than 1 mg, are combined with post-flight Best Estimate Trajectory (BET) information and predicted, flight-substantiated Orbiter aerodynamics to provide determinations up to altitudes of 95 km. In some instances, alternate accelerometry data with micro-g resolution were utilized to extend the data base well into the thermosphere. Though somewhat limited, the ensemble of flights permit a reasonable sampling of monthly, seasonal, and latitudinal variations which can be utilized for atmospheric science investigations and model evaluations and upgrades as appropriate. More significantly, the unparallel vertical resolution in the Shuttle-derived results indicate density shears normally associated with internal gravity waves or local atmospheric instabilities. Consequently, these atmospheres can also be used as stress-atmospheres for Guidance, Navigation and Control (GN and C) system development and analysis as part of any advanced space vehicle design activities.
Explosive decomposition of hydrazine by rapid compression of a gas volume
In the present investigation of the initiation mechanism and the explosion mode of hydrazine decomposition, a 20 cm-long column of liquid hydrazine was accelerated into a column of gaseous nitrogen, from which it was separated by a thin Teflon diaphragm, in a close-ended cylindrical chamber. Video data obtained reveal the formation of a froth generated by the acceleration of hydrazine into nitrogen at the liquid hydrazine-gaseous nitrogen interface. The explosive hydrazine decomposition had as its initiation mechanism the formation of a froth at a critical temperature; the explosion mode of hydrazine is a confined thermal runaway reaction.
Maximum normalized acceleration as a flying qualities parameter
In 1984, Maximum Normalized Rate (MNR) was presented as a Flying Qualities parameter. Subsequent analysis of data from ground based simulation and flight test revealed the utility of a companion parameter, Maximum Normalized Acceleration (MNA). MNR and MNA profiles reveal the presence of both continuous and pulsed compensation strategies during discrete attitude tracking. In addition, MNR appears to be a suitable metric for pilot opinion in the LATHOS data base, while the MNR/MNA relationship is sensitive to pilot-induced-oscillation (PIO) and roll ratcheting problems. As part of an investigation of this problem, Northrop has developed an analysis technique known as the Step Target Method. The Step Target method is essentially a one degree-of-freedom simulation, where an attitude command in the form of a step function is presented to a closed-loop pilot/aircraft model. The two parameters MNR and MNA were shown to be useful in Flying Qualities analysis. MNR was shown to correlate with Pilot Opinion Rating in the LATHOS data base, while MNA reflects PIO and roll ratcheting. Profiles of MNR versus MNA reveal the presence of pulsed compensation strategies in both ground based and in-flight simulation. Furthermore, comparison of continuous and discrete attitude tracking simulation data reveals that these two tracking tasks exhibit independent sensitivities to aircraft characteristics.
Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models: Preprint
Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Lab based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Field surveyed data is critical to assess the performance of component lifetime. Using a documented field survey protocol, 13 field surveys where conducted. Each measurement is encoded with it's spatial location in respect to the other modules. By combining field survey data on degradation predictors with real time satellite weather data, data-driven predictive models of backsheet degradation were trained. LOESS models were constructed to investigate the spatial dependence of measurements. It was found that micro-climatic effects like treelines, ground surface changes, and elevation changes effected the magnitude and variance of the measurements. A GAM model was created to predict the value of degradation based on measured predictors. The model includes variables on the climate of the system and the location of each measurement in the PV mounting structure. The model performed well with an adj:R2 of 0:95 for yellowness index prediction. The model was cross-validated using k-folds.
MuSIKAL: Multiphysics Simulations and Knowledge Discovery Through AI/ML Technologies (Final Technical Report)
Under the MuSiKAL project, we developed a framework for a coastal digital twin (DT) platform capable of integrating diverse data resources, configuring multiscale model simulations, performing SciML‐accelerated predictions, with applications primarily driven by storm surge and heavily rainfall events impacting the Gulf Coast of the U.S.
An implementation of a tree code on a SIMD, parallel computer
We describe a fast tree algorithm for gravitational N-body simulation on SIMD parallel computers. The tree construction uses fast, parallel sorts. The sorted lists are recursively divided along their x, y and z coordinates. This data structure is a completely balanced tree (i.e., each particle is paired with exactly one other particle) and maintains good spatial locality. An implementation of this tree-building algorithm on a 16k processor Maspar MP-1 performs well and constitutes only a small fraction (approximately 15%) of the entire cycle of finding the accelerations. Each node in the tree is treated as a monopole. The tree search and the summation of accelerations also perform well. During the tree search, node data that is needed from another processor is simply fetched. Roughly 55% of the tree search time is spent in communications between processors. We apply the code to two problems of astrophysical interest. The first is a simulation of the close passage of two gravitationally, interacting, disk galaxies using 65,636 particles. We also simulate the formation of structure in an expanding, model universe using 1,048,576 particles. Our code attains speeds comparable to one head of a Cray Y-MP, so single instruction, multiple data (SIMD) type computers can be used for these simulations. The cost/performance ratio for SIMD machines like the Maspar MP-1 make them an extremely attractive alternative to either vector processors or large multiple instruction, multiple data (MIMD) type parallel computers. With further optimizations (e.g., more careful load balancing), speeds in excess of today's vector processing computers should be possible.
Test equipment data package for the KC-135 fiber pulling apparatus
The Fiber Pulling Apparatus (FPA) is a device designed to produce continuous glass fibers from simulated lunar soil, and to determine the effects of reduced gravity, specifically 1/6 g on fiber formation and resultant properties. Briefly, pre-melt simulated lunar soil will be placed in a pint crucible and heated to 1200 C or higher, up to a maximum temperature of 1400 C. At a given temperature, a quartz fiber will be immersed into the melt and then pulled through a chill block and wound onto a cylindrical bobbin using a servo motor control. A high resolution video camera will record the fiber as it is being pulled. This assembly wil be enclosed in Plexiglas. Before fiber pulling commences, the apparatus will be backfilled with dry nitrogen. A separate data acquisition system will support this apparatus. This system will contain a personal computer, video recorder, and monitor. Temperature, acceleration, winding speed, and video images will be controlled and recorded using the data acquisition system. Thus, the FPA will consist of two hardware packages, the fiber production assembly and the data acquisition rack. The primary objective of this test is to determine the effects of 1/6 g on the formation of continuous glass fiber made from simulated lunar soil. Baseline studies using the FPA on the ground will provide a reference for the 1/6 g studies. Of particular interest will be the effect of 1/6 g on the free fluid zone where the fiber exits the crucible. In the fiber spinning parlance this zone is known as the upper jet region, where the boundary slope is greater than one tenth. The properties of the resulting glass fiber will depend on the jet shape as well as distributions of velocity, temperature and tension within the jet. It is unknown at this time how 1/6 g will effect these parameters.