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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Poster — Thur Eve — 70: Automatic lung bronchial and vessel bifurcations detection algorithm for deformable image registration assessment

Purpose: To investigate an automatic bronchial and vessel bifurcations detection algorithm for deformable image registration (DIR) assessment to improve lung cancer radiation treatment. Methods: 4DCT datasets were acquired and exported to Varian treatment planning system (TPS) EclipseTM for contouring. The lungs TPS contour was used as the prior shape for a segmentation algorithm based on hierarchical surface deformation that identifies the deformed lungs volumes of the 10 breathing phases. Hounsfield unit (HU) threshold filter was applied within the segmented lung volumes to identify blood vessels and airways. Segmented blood vessels and airways were skeletonised using a hierarchical curve-skeleton algorithm based on a generalized potential field approach. A graph representation of the computed skeleton was generated to assign one of three labels to each node: the termination node, the continuation node or the branching node. Results: 320 ± 51 bifurcations were detected in the right lung of a patient for the 10 breathing phases. The bifurcations were visually analyzed. 92 ± 10 bifurcations were found in the upper half of the lung and 228 ± 45 bifurcations were found in the lower half of the lung. Discrepancies between ten vessel trees were mainly ascribed to large deformation and in regions where the HU varies. Conclusions: We established an automatic method for DIR assessment using the morphological information of the patient anatomy. This approach allows a description of the lung's internal structure movement, which is needed to validate the DIR deformation fields for accurate 4D cancer treatment planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Materials design of perovskite solid solutions for thermochemical applications

Perovskites are excellent candidate materials as oxygen carriers in thermochemical processes. Due to their versatile composition, it is possible to fine-tune the perovskite's properties. Here, we present a method for the rational design of AMO 3– δ perovskite solid solutions with two different species on the Msite in order to tune their redox behavior. To account for the different ionic radii of different transition metal species M, two distinct ions are used in a solid solution on the A site, allowing tolerance-factor adjusted materials design. Using this methodology, we can create stable perovskites over a large range of different compositions. Leveraging the infrastructure of Materials Project, we calculate redox enthalpies for the reduction of over 240 of these $(\text {A}^{\prime}_x\text {A}^{\prime\prime}_{1-x})(\text {M}^{\prime}_y\text {M}^{\prime\prime}_{1-y})$O 3 perovskites to their brownmillerite phases based on density functional theory (DFT). We compare this data to experimentally measured data on thermodynamics of 24 of these materials to verify our theoretical framework. An empirical model is formulated for predicting the enthalpy and entropy changes as a function of the perovskites non-stoichiometry δ , which can be used to simulate the equilibrium composition as a function of temperature and oxygen partial pressure and to create a perovskite search engine based on an energetic analysis of the redox cycles. The data has been added as a contribution to MPContribs, which now includes publicly available user-controlled interactive graphs based on our theoretical and experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

wa-hls4ml and lui-gnn: A benchmark and GNN-based surrogate model for hls4ml resource and latency estimation

As machine learning (ML) increasingly serves as a tool for addressing real-time challenges in scientific applications, the development of advanced tooling has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as model synthesis, are now becoming limiting factors in the rapid iteration of designs. To reduce these emerging constraints, multiple efforts are being launched toward designing an ML-based surrogate model that estimates resource usage of synthesized accelerator architectures. This model would reduce the design iteration time, especially when designing within a set of given hardware constraints. This approach shows considerable potential, but as it stands, the effort is early and would benefit from coordination and standardization to assist future work as it emerges. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of more than 100,000 fully connected neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. In addition to the resource utilization and latency data provided, the dataset includes generated artifacts and log files for many of the synthesized neural networks, in order to support future research in ML-based code generation. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, as well as the average performance across a subset of the dataset. We measure the performance of a given predictor model through multiple metrics, including $R^2$ score and SMAPE on regression tasks, as well as inference time to further characterize the estimator under test. Additionally, we introduce the latency/utilization inference graph neural network (lui-gnn), a surrogate model that uses a graph neural network to represent input architectures in the form of a directed graph. This graph representation allows for a diverse set of model architectures to all be effectively handled by a surrogate model. We present the architecture and performance of the model, as evaluated by the new proposed benchmark, including SMAPE, $R^2$ score, and inference times, and find that lui-gnn generally predicts latency and utilization for the 75\% quantile within several percent of the synthesized resources on the synthetic test dataset, indicating that this approach of estimating resource and latency via a surrogate models has promise and warrants further research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Development of In-Situation Radioactivity Inspection System for Food Materials

The impacts on the ocean of releases of radionuclides from the Fukushima nuclear power plants remain unclear. Korean people worry about radioactive contamination of Japanese and Korean sea products. Radioactive contamination of processed foodstuffs, livestock, sea products, farm products imported from Japan and fishes caught in coastal oceans of Korea has become an important social issue. Recently, there are also needs of inspection system for monitoring of public meals such like school feedings of kindergarten, elementary/middle/high school and university. Radioactivity inspections of food materials have been executed manually with portable measuring instruments or at labs using their samples. But, it's very important the radioactivity inspection should be performed at the field of feeding facilities. To protect the health of people from radioactivity contained in Japanese marine products imported to Korea, a system to inspect radioactivity in real time has been developed. The system is to measure the radioactivity level of farm and marine products and public meals continuously and automatically at inspection sites of an agency checking radiation of imported foodstuffs or school. The performance test of NaI(Tl) detector was examined using the quantified Cs-137 source 10 Bq/kg, 30 Bq/kg, 50 Bq/kg, 300 Bq/kg and 900 Bq/kg at Korea Research Institute of Standards and Science(KRISS). Source was put in a box and radioactivity was measured in the middle of the box. First of all, Background was measured and calibration was performed using the Cs-137 300 Bq and Ba-133 3700 Bq for 60 minutes. After setting the background and calibration data, tests of the Cs-137 10, 30, 50, 300, 900 Bq/kg were executed for 10 minutes. A peak-shaped graph is shown at the location of 662 KeV (80∼100 channel). This is due to the gamma radiation energy with 662 KeV emitted by the Cs-137. Because through KRISS examination, the MDA (minimum detectable activity) is about 23 Bq/kg, it is reasonable Cs-137 10 Bq/kg cannot be measured. And in cases of Cs-137 300 Bq/kg and 900 Bq/kg, there are some peak movement on the graph. It can be adjusted by controlling gain or high voltage. The examination was identified through the performance test (Cs-137 10, 30, 50, 300, 900 Bq/kg) at KRISS. In order to increase the measurement efficiency of Cs-137 and the system performance, database will be built up based on radioactivity measurement results from 10 to 300 Bq/kg with the unit 10. Thus, Cs-137 concentration of food materials can be identified below the maximum permissible concentration of 100 Bq/kg on a basis of the spectrum characteristic of Cs-137. Also, anxiety about radioactive contamination of foods after the Fukushima nuclear accident will be eased and trust of the radioactive inspection is expected definitely. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

MODEL OF THE FIELD LINE RANDOM WALK EVOLUTION AND APPROACH TO ASYMPTOTIC DIFFUSION IN MAGNETIC TURBULENCE

The turbulent random walk of magnetic field lines plays an important role in the transport of plasmas and energetic particles in a wide variety of astrophysical situations, but most theoretical work has concentrated on determination of the asymptotic field line diffusion coefficient. Here we consider the evolution with distance of the field line random walk using a general ordinary differential equation (ODE), which for most cases of interest in astrophysics describes a transition from free streaming to asymptotic diffusion. By challenging theories of asymptotic diffusion to also describe the evolution, one gains insight on how accurately they describe the random walk process. Previous theoretical work has effectively involved closure of the ODE, often by assuming Corrsin's hypothesis and a Gaussian displacement distribution. Approaches that use quasilinear theory and prescribe the mean squared displacement ({Delta}x {sup 2}) according to free streaming (random ballistic decorrelation, RBD) or asymptotic diffusion (diffusive decorrelation, DD) can match computer simulation results, but only over specific parameter ranges, with no obvious 'marker' of the range of validity. Here we make use of a unified description in which the ODE determines ({Delta}x {sup 2}) self-consistently, providing a natural transition between the assumptions of RBD and DD. We find that the minimum kurtosis of the displacement distribution provides a good indicator of whether the self-consistent ODE is applicable, i.e., inaccuracy of the self-consistent ODE is associated with non-Gaussian displacement distributions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models

Abstract We evaluate the ability of machine learning to predict whether a hypothetical crystal structure can be synthesized and explain those predictions to scientists. Fine‐tuned large language models (LLMs) trained on a human‐readable text description of the target crystal structure perform comparably to previous bespoke convolutional graph neural network methods, but better prediction quality can be achieved by training a positive‐unlabeled learning model on a text‐embedding representation of the structure. An LLM‐based workflow can then be used to generate human‐readable explanations for the types of factors governing synthesizability, extract the underlying physical rules, and assess the veracity of those rules. These explanations can guide chemists in modifying or optimizing non‐synthesizable hypothetical structures to make them more feasible for materials design.

Kim, Seongmin [Department of Chemical and Biologic↗
DOE OSTI2025

Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models

Abstract We evaluate the ability of machine learning to predict whether a hypothetical crystal structure can be synthesized and explain those predictions to scientists. Fine‐tuned large language models (LLMs) trained on a human‐readable text description of the target crystal structure perform comparably to previous bespoke convolutional graph neural network methods, but better prediction quality can be achieved by training a positive‐unlabeled learning model on a text‐embedding representation of the structure. An LLM‐based workflow can then be used to generate human‐readable explanations for the types of factors governing synthesizability, extract the underlying physical rules, and assess the veracity of those rules. These explanations can guide chemists in modifying or optimizing non‐synthesizable hypothetical structures to make them more feasible for materials design.

Kim, Seongmin [Department of Chemical and Biologic↗
DOE OSTI2016

Magnetic field line random walk in isotropic turbulence with varying mean field

In astrophysical plasmas, the magnetic field line random walk (FLRW) plays an important role in guiding particle transport. The FLRW behavior is scaled by the Kubo number R=(b/B{sub 0})(ℓ{sub ∥}/ℓ{sub ⊥}) for rms magnetic fluctuation b, large-scale mean field B{sub 0}, and coherence scales parallel (ℓ{sub ∥}) and perpendicular (ℓ{sub ⊥}) to B{sub 0}. Here we use a nonperturbative analytic framework based on Corrsin’s hypothesis, together with direct computer simulations, to examine the R-scaling of the FLRW for varying B {sub 0} with finite b and isotropic fluctuations with ℓ{sub ∥}/ℓ{sub ⊥}=1, instead of the well-studied route of varying ℓ{sub ∥}/ℓ{sub ⊥} for b ≪B{sub 0}. The FLRW for isotropic magnetic fluctuations is also of astrophysical interest regarding transport processes in the interstellar medium. With a mean field, fluctuations may have variance anisotropy, so we consider limiting cases of isotropic variance and transverse variance (with b {sub z} = 0). We obtain analytic theories, and closed-form solutions for extreme cases. Padé approximants are provided to interpolate all versions of theory and simulations to any B {sub 0}. We demonstrate that, for isotropic turbulence, Corrsin-based theories generally work well, and with increasing R there is a transition from quasilinear to Bohm diffusion. This holds even with b {sub z} = 0, when different routes to R→∞ are mathematically equivalent; in contrast with previous studies, we find that a Corrsin-based theory with random ballistic decorrelation works well even up to R = 400, where the effects of trapping are barely perceptible in simulation results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Temporal Analysis and Scene Change Detection in Multispectral Overhead Imagery

Scene change detection can be a tedious and time consuming process especially when concerning large geographical areas, and the process can be even more cumbersome when analyzing changes in an area over large spans of time. Developing a useful way to help analysts recognize at what points in time significant changes to a scene have occurred can allow them to better focus their efforts in characterizing events. Applications include: Facility monitoring, Construction chronology, Monitoring of vehicle/aircraft activity, Characterization of larger sequences of events. In large areas exceeding hundreds to thousands of square kilometers in size, it can be difficult localizing when scene changes have occurred. Analysts can spend hours going through imagery to try to identify new construction, monitor facility activities, monitor vehicle movement, etc. where the object of interest may only be a few square meters. Our goal is to help cut down this time by giving analysts change maps with hot spots of change, allowing them to focus on regions that have experienced actual change in time frames they're interested in. Additionally, by combining these change maps into layers within a data cube, analysts can examine the change maps from a temporal perspective, allowing events to be characterized over spans of time. By opening the data cube in an imaging software capable of separating the layers, we can analyze the change maps sequentially, allowing us to examine scene changes occurring over time. As an example, we examined overhead imagery from Planet Labs of what appears to be a parking lot on Fort Irwin over the course of a year using ENVI, a geospatial satellite imagery analysis software. Using ENVI, we generate a graph of changes over time, and notice a particular segment near the end of our analysis window where no changes are detected. Examination of the actual satellite imagery reveals that during this time span, the parking lot was empty. This could be due to facility shutdown for maintenance or upgrades, or possibly even total workforce/vehicle fleet movement. Information like this could help analysts better characterize events, as well as to help create clearer timelines in larger sequences of events. Workflow steps: - Collect multiple maps of the same AOI (Area of Interest) during a time span of interest; - Generate change maps from AOI maps; - Generate data cube from change maps. An analyst can use the data cube to help inspect an AOI for activities within a time span of interest. If an event of interest is discovered, the analyst can then refer to the maps corresponding to the appropriate dates and times in the data cube to see precisely what is transpiring. The biggest objective being worked on is improving the change detection methodology employed. We currently use PCA-EM (Principal Component Analysis with Expectation Maximization), but we are currently focusing on implementing IR-MAD (Iteratively Reweighted Multivariate Alteration Detection) to be used in conjunction with PCA-EM in an effort to decrease false positivity and noise in the change maps we generate.

42 ENGINEERING↗
DOE OSTI2014

Final Report for Project DE-FC02-06ER25755 [Pmodels2]

In this report, we describe the research accomplished by the OSU team under the Pmodels2 project. The team has worked on various angles: designing high performance MPI implementations on modern networking technologies (Mellanox InfiniBand (including the new ConnectX2 architecture and Quad Data Rate), QLogic InfiniPath, the emerging 10GigE/iWARP and RDMA over Converged Enhanced Ethernet (RoCE) and Obsidian IB-WAN), studying MPI scalability issues for multi-thousand node clusters using XRC transport, scalable job start-up, dynamic process management support, efficient one-sided communication, protocol offloading and designing scalable collective communication libraries for emerging multi-core architectures. New designs conforming to the Argonne’s Nemesis interface have also been carried out. All of these above solutions have been integrated into the open-source MVAPICH/MVAPICH2 software. This software is currently being used by more than 2,100 organizations worldwide (in 71 countries). As of January ’14, more than 200,000 downloads have taken place from the OSU Web site. In addition, many InfiniBand vendors, server vendors, system integrators and Linux distributors have been incorporating MVAPICH/MVAPICH2 into their software stacks and distributing it. Several InfiniBand systems using MVAPICH/MVAPICH2 have obtained positions in the TOP500 ranking of supercomputers in the world. The latest November ’13 ranking include the following systems: 7th ranked Stampede system at TACC with 462,462 cores; 11th ranked Tsubame 2.5 system at Tokyo Institute of Technology with 74,358 cores; 16th ranked Pleiades system at NASA with 81,920 cores; Work on PGAS models has proceeded on multiple directions. The Scioto framework, which supports task-parallelism in one-sided and global-view parallel programming, has been extended to allow multi-processor tasks that are executed by processor groups. A quantum Monte Carlo application is being ported onto the extended Scioto framework. A public release of Global Trees (GT) has been made, along with the Global Chunks (GC) framework on which GT is built. The Global Chunks (GC) layer is also being used as the basis for the development of a higher level Global Graphs (GG) layer. The Global Graphs (GG) system will provide a global address space view of distributed graph data structures on distributed memory systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

ASK Magazine; No. 21

THIS ISSUE FEATURES A VISUAL DEPICTION OF THE ACADEMY of Program and Project Leadership (APPL). I imagine a variety of initial reactions to the drawing. One might be, "What is a cartoon doing in a magazine about project management?" Or perhaps, "Wow, nice colors-and fun." Another may be to closely search the image for signs, symbols and meaning. Still another, to read a new level of innovation and creativity into the picture. Undoubtedly, some readers will raise questions about the cost. Of course, any reaction is a sign of engagement. The stronger, the more energized the emotional and cognitive processing, the better. It is a sign of attention and interaction. For I've heard it said, "You only need to worry if they don t care one way or the other." So what is the point of the picture? To stimulate interest, raise questions, promote discussion, and maybe raise a smile.. .That, at least, was my initial reaction when I was introduced to the work of Nancy Hegedus, who helps to create these drawings for Root Learning Inc. At the NASA PM Conference, I was first shown the work Nancy had been doing with the help of Goddard s Knowledge Management Architect, Dr. Ed Rogers. I was immediately drawn into the power of visualization as a tool for more effective learning, communicating, and conveying complex knowledge concepts. We need new tools in today s world, where information and data overwhelms by sheer volume. There are articles, pamphlets, communications, and white papers-all aiming to convince and influence. Reactions to these tend to be either avoidance or mind-numbing, heavy-eyed consent; the message never registers or enters the soul. That s one of the reasons that APPL s Knowledge Sharing Initiative (KSI) has turned to storytelling as a memorable way of transfer- ring knowledge, inspiring imitation of best practices, and spurring reflection. ASK Magazine s recent fourth birthday marks an important milestone in APPL s continuing quest to provide ongoing support to project managers and to promote mission success. And similar to storytelling, the power of visualization is receiving increasing attention in recent years as a way to stimulate engagement. Pictures and visual graphs are viewed as one of the most effective ways for displaying, describing, and generating discussion about quantitative and technically complex information. Prototypes, models, and simulations are considered essential for stimulating innovation through open and engaging discussions. There has also been extensive writing on the use of visual graphics, pictures, and cartoons to facilitate memory, creativity, openness, attention-and even well-being. For many of these reasons, I am excited to have a colorful visual depiction of the APPL world included in ASK. Without the addition of text or slides, the intent is to invite people into the world of the APPL mission-as well as its products, services, customers, and partners- in a fun and engaging manner. As project leaders strive to find ways to encourage engagement, learning, and transmission of knowledge, traditional technologies are proving to be as valuable as modern technologies. (But for those who want more information in the form of texts and slide presentations, we certainly have an abundance of those as well.)

Laufer, Alexander↗
DOE OSTI2016

SU-F-I-59: Quality Assurance Phantom for PET/CT Alignment and Attenuation Correction

Purpose: This study utilizes a commercial PET/CT phantom to investigate two specific properties of a PET/CT system: the alignment accuracy of PET images with those from CT used for attenuation correction and the accuracy of this correction in PET images. Methods: A commercial PET/CT phantom consisting of three aluminum rods, two long central cylinders containing uniform activity, and attenuating materials such as air, water, bone and iodine contrast was scanned using a standard PET/CT protocol. Images reconstructed with 2 mm slice thickness and a 512 by 512 matrix were obtained. The center of each aluminum rod in the PET and CT images was compared to evaluate alignment accuracy. ROIs were drawn on transaxial images of the central rods at each section of attenuating material to determine the corrected activity (in BQML). BQML values were graphed as a function of slice number to provide a visual representation of the attenuation-correction throughout the whole phantom. Results: Alignment accuracy is high between the PET and CT images. The maximum deviation between the two in the axial plane is less than 1.5 mm, which is less than the width of a single pixel. BQML values measured along different sections of the large central rods are similar among the different attenuating materials except iodine contrast. Deviation of BQML values in the air and bone sections from the water section is less than 1%. Conclusion: Accurate alignment of PET and CT images is critical to ensure proper calculation and application of CT-based attenuation correction. This study presents a simple and quick method to evaluate the two with a single acquisition. As the phantom also includes spheres of increasing diameter, this could serve as a straightforward means to annually evaluate the status of a modern PET/CT system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

RhizoGrid Indexed Sorghum Rhizosphere Multi-Omics

PerCon SFA project data dentification of spatially resolved biomarkers of drought in Sorghum bicolor rhizosphere molecular-microbe interactions using a novel root cartography "RhizoGrid" system for sampling plants under drought and control conditions across 10 equally sized root zone environments (4 quadrants each). Each quadrant was sampled and processed for 16S amplicon, metabolomics, and X-ray computed tomography (XCT). Data download includes experimental metadata and results files for 16S rRNA sequence analysis of microbial community assembly (processed data files), liquid chromatography mass spectrometry (LC-MS) metabolomics analysis of microbial community root exudates (processed data files), X-ray computed tomography (XCT) spatial gradient analysis (raw and processed data files) of microbial community composition, and related computational modeling outputs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Efficient Parallelization of Irregular Applications on GPU Architectures

With the enlarging computation capacity of general Graphics Processing Units (GPUs), leveraging GPUs to accelerate parallel applications has become a critical topic in academia and industry. However, a wide range of irregular applications with the computation-/memory-intensive nature cannot easily achieve high GPU utilization. The challenges mainly involve the following aspects: first, data dependence leads to coarse-grained kernel and inefficient parallelism; second, heavy GPU memory usage may cause frequent memory evictions and extra overhead of I/O; third, specific computation patterns produce memory redundancies; last, workload balance and data reusability conjunctly benefit the overall performance, but there may exist a dynamic trade-off between them. Targeting these challenges, this dissertation proposes multiple optimizations to accelerate two real-world applications: many-body correlation functions to simulate nuclear physics in a large-scale scientific system; the other is the eALS-based matrix factorization recommendation system. To accelerate the calculations of many-body correlation functions, this dissertation presents three frameworks in GPU memory management and multi-GPU scheduling. Firstly, an optimized systematic GPU memory management framework, MemHC, utilizes a series of new memory reduction designs in GPU memory allocation, CPU/GPU communications, and GPU memory oversubscription. Secondly, an enhanced multi-GPU scheduling framework, MICCO, particularly by taking both data dimension (e.g., data reuse and data eviction) and computation dimension into account. MICCO designs a heuristic scheduling algorithm and a machine learning-based regression model to generate the optimal settings of a proposed new concept to manage the trade-off. Thirdly, a locality-aware multi-GPU scheduling framework. This scheduler leverages pipeline batch generation with a looking-ahead strategy by building local dependency graphs for memory transfer reduction and better data reuse, achieving up to 79.92% memory cost reduction and 1.67x speedup. To parallelize the eALS-based recommendation system, this dissertation proposes an efficient CPU/GPU heterogeneous recommendation system, HEALS. HEALS employs newly designed architecture-adaptive data formats to achieve load balance and good data locality on CPU and GPU. To mitigate the data dependence, HEALS presents a CPU/GPU collaboration model for both task parallelism and data parallelism with multiple kernel computation optimizations. In summary, this dissertation efficiently accelerates two typical irregular applications on GPUs by building four frameworks, including CPU/GPU collaboration, GPU memory management, and multi-GPU scheduling.

Wang, Qihan↗
DOE OSTI2024

The circular bioeconomy: a driver for system integration

Background: Human and earth system modeling, traditionally centered on the interplay between the energy system and the atmosphere, are facing a paradigm shift. The Intergovernmental Panel on Climate Change’s mandate for comprehensive, cross-sectoral climate action emphasizes avoiding the vulnerabilities of narrow sectoral approaches. Our study explores the circular bioeconomy, highlighting the intricate interconnections among agriculture, forestry, aquaculture, technological advancements, and ecological recycling. Collectively, these sectors play a pivotal role in supplying essential resources to meet the food, material, and energy needs of a growing global population. We pose the pertinent question of what it takes to integrate these multifaceted sectors into a new era of holistic systems thinking and planning. Results: The foundation for discussion is provided by a novel graphical representation encompassing statistical data on food, materials, energy flows, and circularity. This representation aids in constructing an inventory of technological advancements and climate actions that have the potential to significantly reshape the structure and scale of the economic metabolism in the coming decades. In this context, the three dominant mega-trends—population dynamics, economic developments, and the climate crisis—compel us to address the potential consequences of the identified actions, all of which fall under the four categories of substitution, efficiency, sufficiency, and reliability measures. Substitution and efficiency measures currently dominate systems modeling. Including novel bio-based processes and circularity aspects might require only expanded system boundaries. Conversely, paradigm shifts in systems engineering are expected to center on sufficiency and reliability actions. Effectively assessing the impact of sufficiency measures will necessitate substantial progress in inter- and transdisciplinary collaboration, primarily due to their non-technological nature. In addition, placing emphasis on modeling the reliability and resilience of transformation pathways represents a distinct and emerging frontier that highlights the significance of an integrated network of networks. Conclusions: Existing and emerging circular bioeconomy practices can serve as prime examples of system integration. These practices facilitate the interconnection of complex biomass supply chain networks with other networks encompassing feedstock-independent renewable power, hydrogen, CO 2 , water, and other biotic, abiotic, and intangible resources. Elevating the prominence of these connectors will empower policymakers to steer the amplification of synergies and mitigation of tradeoffs among systems, sectors, and goals.

09 BIOMASS FUELS↗
DOE OSTI2019

Electric Conductivity of TiO{sub 2}-Ti{sub 2}O{sub 3}-FeO-CaO-SiO{sub 2}-MgO-Al{sub 2}O{sub 3} for High-Titania Slag Smelting Process

The electric conductivity of high-titania slag of TiO{sub 2}-Ti{sub 2}O{sub 3}-FeO-CaO-SiO{sub 2}-Al{sub 2}O{sub 3}-MgO slag system was measured by means of four-electrode alternating current (AC) impedance method. The results show that high-titania slag exhibits a good electric conductivity, around 45 to 141 S cm{sup −1} with slight dependence on the temperature, which is of several orders of magnitude higher than that of the silicate slags. Further, electric conductivity of high-titania slag decreased with the increasing FeO content, whereas, the increasing Ti{sup 3+}/Ti{sup 4+} and TiO{sub 2} contents caused a significant increase in the electric conductivity. Based on the experimental results and the calculated results, the conductive mechanism of high-titania slag was discussed in detail. It can be concluded that the high-titania slag exhibits a characteristic of electronic–ionic mixed conductivity, but the effect of electronic conduction dominates above the liquidus temperature; however, with the decreasing temperature, the electronic conductivity was gradually weakened. The mechanism was postulated to be a random walk of electrons between tetravalent titanium and trivalent titanium dispersed in the melt.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Bringing Fenton Hill into the Digital Age: Data Conversion in Support of the Geothermal Technologies Office Code Comparison Study Challenge Problems

The Geothermal Technologies Office Code Comparison Study (GTO-CCS) was established by the U.S. Department of Energy to facilitate collaboration among members of the geothermal modeling community and to evaluate and improve upon the ability of existing codes to simulate thermal, hydrological, mechanical, and chemical processes associated with complex enhanced geothermal systems (EGS). The first stage of the project, which has been completed, involved comparing simulations for seven benchmark problems that were primarily designed using well-prescribed, simplified data sets. In the second stage, the participating teams are tackling two challenge problems based on the EGS research conducted in hot dry rock (HDR) at Fenton Hill, near Los Alamos, New Mexico. The Fenton Hill project, conducted by Los Alamos National Laboratory (LANL) from 1970 to 1995, was the world’s first HDR demonstration project. One of the criteria for selecting this experiment as the basis for the challenge problems was the amount and availability of data for generating model inputs. The Fenton Hill HDR system consisted of two reservoirs – an earlier Phase I reservoir tested from 1974 to 1981 and a deeper Phase II reservoir tested from 1980 to 1995. Detailed accounts of both phases of the HDR project have been presented in a number of books and reports, including a recently published summary of the lessons learned and a final report with a chronological description of the Fenton Hill project, prepared by LANL. Project documents and records have been archived and made public through the National Geothermal Data System (NGDS). Some of the data acquired from Phase II are available in electronic format readable on modern computers. These include the microseismic data from some of the important experiments (e.g. the massive hydraulic fracturing test conducted in 1983) and the injection/production wellhead data from the circulation tests conducted between 1992-1995. However, much of the data collected during the project, while publicly available, currently only exist in the form of tables or graphs within scanned documents. Therefore, in support of the GTO-CCS, the data needed for developing simulation inputs are being compiled and converted to platform independent, open readable formats so that all participating teams will have access to the same electronic data set. In some cases this requires conversion using optical character recognition, digitizing existing images, and generating the appropriate metadata from project documents. The GTO-Velo knowledge management framework, developed by Pacific Northwest National Laboratory (PNNL), was used for the benchmark problem stage of the comparison study and will also be used as the data repository for the challenge problem data sets. It is staggering and impractical to convert all published data for the Fenton Hill site, so the focus is on data that supports simulations for the three topical areas defined by the study for the challenge problems: 1) reservoir creation/stimulation, 2) reactive and passive transport, and 3) thermal recovery. Conversion of these data provide value not only to GTO-CCS participants, but also to members of the geothermal community at large who may be interested in revisiting the Fenton Hill experiment in the future.

Code Comparison Study↗
DOE OSTI2012

Generalized Environment for Modeling Systems

GEMS is an integrated environment that allows technical analysts, modelers, researchers, etc. to integrate and deploy models and/or decision tools with associated data to the internet for direct use by customers. GEMS does not require that the model developer know how to code or script and therefore delivers this capability to a large group of technical specialists. Customers gain the benefit of being able to execute their own scenarios directly without need for technical support. GEMS is a process that leverages commercial software products with specialized codes that add connectivity and unique functions to support the overall capability. Users integrate pre-existing models with a commercial product and store parameters and input trajectories in a companion commercial database. The model is then exposed into a commercial web environment and a graphical user interface (GUI) is applied by the model developer. Users execute the model through the web based GUI and GEMS manages supply of proper inputs, execution of models, routing of data to models and display of results back to users. GEMS works in layers, the following description is from the bottom up. Modelers create models in the modeling tool of their choice such as Excel, Matlab, or Fortran. They can also use models from a library of previously wrapped legacy codes (models). Modelers integrate the models (or a single model) by wrapping and connecting the models using the Phoenix Integration tool entitled ModelCenter. Using a ModelCenter/SAS plugin (DOE copyright CW-10-08) the modeler gets data from either an SAS or SQL database and sends results back to SAS or SQL. Once the model is working properly, the ModelCenter file is saved and stored in a folder location to which a SharePoint server tool created at INL is pointed. This enables the ModelCenter model to be run from SharePoint. The modeler then goes into Microsoft SharePoint and creates a graphical user interface (GUI) using the ModelCenter WebPart (CW-12-04) created at INL to work inside SharePoint. The GUI tool links slider bars and drop downs to specific inputs and output of the ModelCenter model that is executable from SharePoint. The modeler also creates in SAS, dashboards, graphs and tables that are exposed by links and SAS and ModelCenter Web Parts into the SharePoint system. The user can then log into SharePoint, move slider bars and select drop down lists to configure the model parameters, click to run the model, and then view the output results that are based on their particular input choices. The main point is that GEMS eliminates the need for a programmer to connect and create the web artifacts necessary to implement and deliver an executable model or decision aid to customers.

Alessi, RandolphSamuel↗