Climate Drives Modeled Forest Carbon Cycling Resistance and Resilience in the Upper Great Lakes Region, USA
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Kalyn Dorheim↗
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Satellite Monitoring of Global Surface Soil Organic Carbon Dynamics Using the SMAP Level 4 Carbon Product
Soil organic carbon (SOC) is an important metric of soil health and the terrestrial carbon balance. Short‐term climate variations affect SOC through changes in temperature and moisture, which control vegetation growth and soil decomposition. We evaluated a satellite data‐driven carbon model, operating under the NASA Soil Moisture Active‐Passive (SMAP) mission, as a means of monitoring global surface SOC dynamics. The SMAP Level 4 Carbon (L4C) product estimates a daily global carbon budget including surface (0‐ to 5‐cm depth) SOC. We found that the L4C mean latitudinal SOC distribution is generally consistent with alternative assessments from static soil inventory records and dynamic global vegetation models (r ≥ 0.89). Within forest systems, based on inventory data, L4C SOC is most similar in magnitude to litterfall but is correlated with coarse woody debris ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0001) and total SOC ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0002). L4C SOC is sensitive to seasonal and annual climate variability, with mean residence times that range from 1.5 years in the wet tropics to 17 years in the cold tundra. Incorporating soil moisture retrievals from the SMAP L‐band (1.4 GHz) microwave radiometer within the L4C algorithm provides enhanced soil moisture sensitivity under low‐to‐moderate vegetation cover (<5 kg/sq.m vegetation water content). The L‐band soil moisture had the greatest impact on the L4C carbon budget in semiarid regions, which span almost 60% of the globe and account for substantial variability in the terrestrial carbon sink. The L4C operational product enables prognostic investigations into effects of recent climate trends and anomalies (e.g., droughts and pluvials) on shallow soil carbon dynamics.
K. Arthur Endsley↗
“Lagrangian disks” in M-theory
While the study of bordered (pseudo-)holomorphic curves with boundary on Lagrangian submanifolds has a long history, a similar problem that involves (special) Lagrangian submanifolds with boundary on complex surfaces appears to be largely overlooked in both physics and math literature. We relate this problem to geometry of coassociative submanifolds in G 2 holonomy spaces and to Spin(7) metrics on 8-manifolds with T 2 fibrations. As an application to physics, we propose a large class of brane models in type IIA string theory that generalize brane brick models on the one hand and 2d theories T[M 4 ] on the other.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Developing Nontraditional Partnerships to Disseminate the Space Science Story
NASA Space Science Days (NSSD) was established in 2004 to bring the story of the Mars Exploration Rovers (MER) to a community far removed from areas NASA traditionally serves. The original NSSD invited 400 5th and 8th graders from the Texas Rio Grande Valley area to the University of Texas Brownsville campus to participate in a one day Saturday event filled with information about MER with related hands on activities. Currently the program has grown to over 700 5th and 8th grade participants who are mentored by trained university students from several Texas universities and community colleges and growing to include universities from throughout the U.S. A collaboration between three major institutions: The NASA Johnson Space Center (JSC) Astromaterials Research and Exploration Science Directorate (ARES), the Society of Hispanic Professional Engineers/Advancing Hispanic Excellence in Technology Engineering, Math, and Science, (SHPE/AHETEMS), and the University of Texas at Brownsville (UTB) has been established to enable the dissemination of Solar System related educational materials throughout the U.S. Already in its 8th year, UTB has developed and tested a NSSD model that has successfully disseminated space science materials to students throughout South Texas Rio Grande Valley. With this newly formed collaboration this model s expansion will allow trained SHPE students and professionals to conduct events throughout its established nation-wide delivery systems. Each year a new NSSD site will be established through an application process solicited from SHPE student and professional chapters. Once a chapter is awarded, upper-level high school and university students will travel to NASA- JSC for a two day workshop where students learn about the current year s theme and are trained to present hands-on activities related to the theme. Additional training by ARES and UTB occurs one month before the new event in their own communities. Both local middle school teachers and mentors are trained locally. This allows the teachers time to prepare their students with the background material for NSSD and give the mentors time to decide which activity they feel comfortable with to lead. Several events using this process have already been successful and an increase in interest from SHPE chapters wanting to establish their NSSD event is growing.
Galindo, Charles↗
CAIDA CUI Confirmation for OMRS & LCC SOCRRATES Emulator and iSEE Upgrade, Operations, & Analysis
This internship has focused on providing solutions for the Customer Avionics Interface Development and Analysis (CAIDA) subsystem. The main emulator that has been used during this internship is the Software-Only CEV (Crew Exploration Vehicle) Risk Reduction Analysis and Test Engineering Simulator (SOCRRATES). This emulator uses advanced math and physics methods to simulate specific points in a mission, such as ascent, entry, and orbit. Exploration Ground Systems (EGS) must ensure that all KSC based ground systems can be properly integrated with the flight vehicle software, therefore, the Modeling and Simulation Branch (NE-XM) of the KSC (Kennedy Space Center) Engineering Directorate supports a virtual environment that simulates the interface between ground systems and the flight vehicle. A primary component in assuring that is knowing whether the emulators have incorporated the correct CUIs (Compact Unique Identifiers) into their system, as well as understanding both the static and dynamic responses of the individual CUIs. Also, an effort for verification of Operational Maintenance Requirements Specifications (OMRS) and Launch Commit Criteria (LCC) that are supported by SOCRRATES for the Orion Crew Module were part of the project tasks this semester. This internship also focused on comparing two different simulation Commercial-off-the-shelf (COTS) products and to determine whether or not a COTS package was a viable replacement for the current software that the iSEE (Immersive Simulations and Engineering Environment) lab uses. Upon research and testing, I found that this software was not feasible for the lab. It could not easily load CAD (Computer-Aided Design) or CREO models, give live feedback while the user is in the environment, and was not compatible with a virtual reality headset, all of which are necessary for the lab.
Bundy, Caleb↗
Preparing technicians for engineering materials technology
A long held principle is that for every engineer and scientist there is a need for ten technicians to maximize the efficiency of the technology team for meeting needs of industry and government. Developing an adequate supply of technicians to meet the requirements of the materials related industry will be a challenge and difficult to accomplish. A variety of agencies feel the need and wish to support development of engineering materials technology programs. In a joint effort among Battelle Laboratories, the Department of Energy (DOE) and Northwest College and University Association for Science (NORCUS), the development of an engineering materials technology program for vocational programs and community colleges for the Pacific Northwest Region was recently completed. This effort has implications for a national model. The model Associate of Applied Science degree in Engineering Materials Technology shown provides a general structure. It purposely has course titles which need delimiting while also including a core of courses necessary to develop cognitive, affective and psychomotor skills with the underlining principles of math, science and technology so students have job entry skills, and so that students can learn about and adapt to evolving technology.
Jacobs, James A.↗
CheKiPEUQ Intro 1: Bayesian Parameter Estimation Considering Uncertainty or Error from both Experiments and Theory**
A common goal is extraction of physico-chemical parameter values such as pre-exponentials and activation energies from experiment. Ever increasing knowledge from experiments and computations is enabling semi-quantitative prior predictions of such values. When prior knowledge of physically realistic ranges is available, a method named Bayesian parameter estimation (BPE) enables more physically realistic parameter estimation relative to unsophisticated fitting by seeking the most probable value when considering together the uncertainties from prior knowledge, experimental data, and approximations in the model. An impediment to widespread use of BPE is a lack of understanding, training, and user-friendly software. Along with this invited publication, a general software package for BPE is being released that is user-friendly and that does not require understanding of the math behind the methodology. Overall, two previously unpublished catalysis science examples are provided along with considerations and guidelines for successful application of BPE. Following this work, BPE can become more widespread to enable extraction of physically meaningful parameter values.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)
The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.
36 MATERIALS SCIENCE↗
IRIS-MASH: Efficient Multi-device Asynchronous Multi-Stream Heterogeneous Computing
In the rapidly evolving field of high-performance computing (HPC), effectively leveraging heterogeneous devices through asynchronous task programming is paramount. This paper presents a robust asynchronous task programming model tailored for a multi-device, multi-stream execution environment that incorporates a diverse array of heterogeneous computing units, including GPUs from various vendors and other accelerators. Current state-of-the-art task programming models provide methodologies to support asynchronous task executions, but they typically handle homogeneous devices using native programming languages, while support for heterogeneous devices is limited to frameworks like OpenCL. This gap presents significant challenges in abstracting heterogeneous devices to harness their true asynchronous capabilities effectively using their native programming languages. By implementing asynchronous task execution, our model significantly boosts the performance of tiled algorithm task graphs through overlapping data transfers with computation and enabling the simultaneous execution of multiple kernels. We integrate this approach into a heterogeneous Intelligent Runtime System (IRIS) and assess its performance using a suite of tiled algorithm benchmarks from the heterogeneous math kernels library (MatRIS) based on IRIS. Experimental results demonstrate a performance improvement ranging from 1.6 × to 2 × over IRIS without asynchronous support, and a notable 22% performance enhancement compared to established runtime systems such as StarPU and PaRSEC. This approach significantly improves computation efficiency of HPC workflows and provides a solid base for future exploration and development in the area of asynchronous task programming in heterogeneous systems.
Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗
Deviations from maximal entanglement for eigenstates of the Sachdev-Ye-Kitaev model
We consider mid-spectrum eigenstates of the Sachdev-Ye-Kiteav (SYK) model. We prove that for subsystems whose size is a constant fraction of the system size, the entanglement entropy deviates from the maximum entropy by at least a positive constant. This result highlights the difference between the entanglement entropy of mid-spectrum eigenstates of the SYK model and that of random states.
Disordered Systems and Neural Networks (cond-mat.d↗
Unified aeroacoustics analysis for high speed turboprop aerodynamics and noise. Volume 4: Computer user's manual for UAAP turboprop aeroacoustic code
The Unified AeroAcoustic Program (UAAP) code calculates the airloads on a single rotation prop-fan, or propeller, and couples these airloads with an acoustic radiation theory, to provide estimates of near-field or far-field noise levels. The steady airloads can also be used to calculate the nonuniform velocity components in the propeller wake. The airloads are calculated using a three dimensional compressible panel method which considers the effects of thin, cambered, multiple blades which may be highly swept. These airloads may be either steady or unsteady. The acoustic model uses the blade thickness distribution and the steady or unsteady aerodynamic loads to calculate the acoustic radiation. The users manual for the UAAP code is divided into five sections: general code description; input description; output description; system description; and error codes. The user must have access to IMSL10 libraries (MATH and SFUN) for numerous calls made for Bessel functions and matrix inversion. For plotted output users must modify the dummy calls to plotting routines included in the code to system-specific calls appropriate to the user's installation.
Menthe, R. W.↗
HCN emissions from the explosive volcanic eruption of Mt. Pinatubo, Philippines, in June 1991
In June 1991, Mt. Pinatubo explosively erupted magma and overlying rock, with ejecta reaching stratospheric altitudes. The sulphate aerosol burden resulting from the 1991 eruption was still measurable in 1992 and its complete removal took 5-6 years. Here we present new analyses of measurements by the ATMOS instrument on the Atlas-1 Space Shuttle mission and the MkIV balloon interferometer in 1992 that show about 40-50 ppt of unexpected excess HCN in the middle stratosphere. HCN has no stratospheric sources and a lifetime of several years. Multi-year runs with the GEOS-Chem Chemistry-Transport model have been performed in order to derive the most plausible HCN injection amounts. The overall structure of the modeled HCN agrees reasonably well with observations by MkIV and ATMOS. The current best estimate is an emission of about 6 kt of HCN into the stratosphere at an altitude of about 23 km. This compares to a total gas emission in the order of 70-700 Mt, based on an emission of 14 Mt SO2 and an SO2/total gas ratio of 2% - 20%. We will discuss possible sources and formation mechanisms of the HCN. These include abiotic formation during or prior to the eruption and may involve HCN accumulated in the subaerial volcanic-hydrothermal system of Mt. Pinatubo. We present results from thermochemical equilibrium calculations as well as photochemical plume modeling in order to provide plausibility constraints on the source of the HCN.
Armin Kleinboehl↗
March of the Interns
Summer 2019 brought 70 interns — from Puerto Rico, 44 continental US states, Sweden, and the Republic of Trinidad and Tobago — into the NASA Ames Aeromechanics Branch. Some were high school students learning engineering for the first time, while most were mechanical and aerospace engineering students, though two physics majors and a math major jumped into the mix to provide balance. This year’s interns completed work on 30 different projects with a collective of 30,000 dedicated hours of work. The projects this year were on urban air mobility (UAM), search and rescue vehicle design, all things Mars, Titan exploration concept designs, 3D modeling (i.e. computer aided design, CAD), computational fluid dynamics (CFD), and much more. Last year we addressed the question of what to do with an army of interns. This year, we are following its path to change the world.
Dromiack, Hannah↗
Computational Math Problems for a Clean Energy Future
Cutting edge computational mathematics are ubiquitous in renewable energy research. Problems in resilient and reliable electric grid operations, infrastructure planning, wind farm yaw control, and more demand sophisticated and scalable computational tools that enable the transition of renewable energy technologies from proof of concept to deployment into our energy system. The mission of the Computational Science Center at NREL is to lead the lab's efforts to solve energy challenges using high-performance computing (HPC), computational science, applied mathematics, scientific data management, visualization, and informatics. In this poster, we provide a short overview of three areas of computational mathematics research at NREL: wind power scenario generation for stochastic grid operations and infrastructure planning, improved rational function approximations for electromagnetic transients codes, and wind farm yaw control using a combination of the Alternating Direction Method of Multipliers (ADMM) and reinforcement learning (RL). Increasing penetrations of renewable energy into power grids motivate the investigation of new approaches to characterizing uncertainty for five-minute economic dispatch problems. Similarly, as the penetration of distributed energy resources on power grids increases, it becomes important to revisit our methods of modelling transient phenomena, i.e. electromagnetic transients programs. Finally, the combination of ADMM and RL for wind farm yaw control presented here can potentially increase the efficiency of the deployed distributed controllers by orders of magnitude.
ADMM↗
Using Likwid and Byfl to Benchmark Hardware Performance
This paper outlines a benchmarking study conducted during my internship at LANL, focusing on CPU (Computer Processing Unit) and program performance assessment. The primary goal was to gather memory access data using three methods across five polybench kernels The data gathered would then be used to compare and contrast to one another and calculate operational intensity for performance comparisons. Benchmarking tools like Byfl and Likwid were employed, with Byfl offering hardware-independent data through LLVM compiler communication and Likwid directly interacting with computer hardware. The study considered various benchmarking factors, including optimization levels, Big O notation ((n)), CPU diversity and specific kernel equations. Big O notation was utilized to simplify code complexity, with detailed breakdwons of operations and memory components for each polybench application. Specific O(n) equations enabled nuanced kernel compariosns, facilitating the identification of performance variations. CPU efficiency assessments were conducted using Likwid tests on two CPUs. The central focus on code optimization aimed at achieving higher speeds and reduced memory usage through streamlined code. Future work propsoes creating a roofline model, synthesizing benchmarking data into a comprehensive data graph to assist in optimizing code and improving hardware performance. The potential impact on the laboratory or national mission was underscored, emphasizing the importance of optimizing applications and hardware to conserve resources and accelerate program execution. The specific relevance to LANL’s operations in math-intensive fields such as Nuclear Fission, Space Exploration, and Nanotechnology highlights the necessity of efficient benchmarking for resource conservation and proram speed. Overall, this study contributes to the understanding of CPU and program performance, providing insights for future optimization efforts in a laboratory setting
97 MATHEMATICS AND COMPUTING↗
Verification of an improved equation-free projective integration method for neoclassical plasma-profile evolution in tokamak geometry
A brute-force, long-time gyrokinetic simulation of plasma profile evolution in magnetic fusion devices is not desirable due to large computational resource requirements and a possible accumulation of numerical error. The equation-free projective integration method of Keverekidis et al. [Commun. Math. Sci. 1(4), 715–762 (2003)] is one of the outstanding candidates in projecting micro-scale simulations to a longer timescale. However, its application to tokamak plasma has not been fruitful due to the appearance of spurious transient oscillations in the lifting process, which are present when the kinetic simulations are initialized with a simplified model distribution function and which make the kinetic simulations to deviate from the desired paths. In this work, a kinetically informed lifting algorithm is added to the equation-free projective integration method, which is then verified in the electrostatic gyrokinetic particle-in-cell code XGCa [R. Hager and C. S. Chang, Phys. Plasmas 23, 042503 (2016)] for a neoclassical ion heat transport problem with adiabatic electrons. This new lifting operator is demonstrated to control spurious transients, enabling an over four-times reduction in the overall computing time in the time-evolution of the ion temperature profile in an axisymmetric toroidal plasma. Further reduction in the computing time is found to be limited due to the stability properties of the linear least squares projective integrator.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
SynGenics Optimization System (SynOptSys)
The SynGenics Optimization System (SynOptSys) software application optimizes a product with respect to multiple, competing criteria using statistical Design of Experiments, Response-Surface Methodology, and the Desirability Optimization Methodology. The user is not required to be skilled in the underlying math; thus, SynOptSys can help designers and product developers overcome the barriers that prevent them from using powerful techniques to develop better pro ducts in a less costly manner. SynOpt-Sys is applicable to the design of any product or process with multiple criteria to meet, and at least two factors that influence achievement of those criteria. The user begins with a selected solution principle or system concept and a set of criteria that needs to be satisfied. The criteria may be expressed in terms of documented desirements or defined responses that the future system needs to achieve. Documented desirements can be imported into SynOptSys or created and documented directly within SynOptSys. Subsequent steps include identifying factors, specifying model order for each response, designing the experiment, running the experiment and gathering the data, analyzing the results, and determining the specifications for the optimized system. The user may also enter textual information as the project progresses. Data is easily edited within SynOptSys, and the software design enables full traceability within any step in the process, and facilitates reporting as needed. SynOptSys is unique in the way responses are defined and the nuances of the goodness associated with changes in response values for each of the responses of interest. The Desirability Optimization Methodology provides the basis of this novel feature. Moreover, this is a complete, guided design and optimization process tool with embedded math that can remain invisible to the user. It is not a standalone statistical program; it is a design and optimization system.
Ventresca, Carol↗
Expanding your horizons in science and mathematics
Through the presentation of its Expanding Your Horizons in Science and Mathematics career education conferences for secondary school young women, the Math/Science Network continues its efforts to remove the educational, psychological, and cultural barriers which prevent women from entering math-and science-based careers. The Expanding Your Horizons conferences were presented on 77 college, university and high school campuses across the United States. This year, these unique one day conferences reached 15,500 students, 3,000 parents and educators, and involved 3,000 career women who volunteered their services as conference planners, workshop leaders, speakers, and role models.
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