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In a future age, the Biocene, our descendants will look back at the present. They will see evidence, in the geologic and electronic record, of anthropic climate change, conflict, and scarcity of resources. But they will also see the emergence of new life, the rebirth of human ingenuity and of empathy as we overcame the challenges that faced us through convergence and nature-inspired exploration.
The rescue crews have been searching for the woman for nearly a week. Hurricane Katrina devastated Hancock County, the southernmost point in Mississippi, and the woman had stayed through the storm in her beach house. There is little hope of finding her alive; the search teams know she is gone because the house is gone. Late at night in the art classroom of the school that is serving as the county s emergency operations center, Craig Harvey is discussing the search with the center s commander. Harvey is the Chief Operating Officer of a unique company called NVision Solutions Inc., based at NASA s Stennis Space Center in Bay St. Louis, only a couple of miles away. He and his entire staff have set up a volunteer operation in the art room, supporting the emergency management efforts using technology and capabilities the company developed through its NASA partnerships. As he talks to the commander, Harvey feels an idea taking shape that might lead them to the woman s location. Working with surface elevation data and hydrological principles, Harvey creates a map showing how the floodwaters from the storm would have flowed along the topography of the region around the woman s former home. Using the map, search crews find the woman s body in 15 minutes. Recovering individuals who have been lost is a sad reality of emergency management in the wake of a disaster like Hurricane Katrina in 2005. But the sooner answers can be provided, the sooner a community s overall recovery can take place. When damage is extensive, resources are scattered, and people are in dire need of food, shelter, and medical assistance, the speed and efficiency of emergency operations can be the key to limiting the impact of a disaster and speeding the process of recovery. And a key to quick and effective emergency planning and response is geographic information. With a host of Earth-observing satellites orbiting the globe at all times, NASA generates an unmatched wealth of data about our ever-changing planet. This information can be captured, analyzed, and visualized by geographic information systems (GIS) to produce maps, charts, and other tools that can reveal information essential to a wide variety of applications including emergency management. Knowing precise, real-time information about the size, location, environmental conditions, and resulting damage of an event like a flood or wildfire as well as the location and numbers of emergency responders and other resources contributes directly to the effectiveness of disaster mitigation. The need for such information is also evident when responding to homeland security threats, such as a terrorist attack. Recognizing the value of its geospatial information resources for this and other purposes, in 1998 Stennis and the state of Mississippi partnered to form what became the Enterprise for Innovative Geospatial Solutions (EIGS) industry cluster, supporting the growth of remote sensing and GIS-based research and business. As part of EIGS, several companies partnered with NASA through dual use and Small Business Innovation Research (SBIR) contracts. Among those was NVision.
Here, a review of current trends in scientific computing reveals a broad shift to open-source and higher-level programming languages such as Python and growing career opportunities over the next decade. Open-source modeling tools accelerate innovation in equation-based and data-driven applications. Significant resources have been deployed to develop data-driven tools (PyTorch, TensorFlow, Scikit-learn) from tech companies that rely on machine learning services to meet business needs while keeping the foundational tools open. Open-source equation-based tools such as Pyomo, CasADi, Gekko, and JuMP are also gaining momentum according to user community and development pace metrics. Integration of data-driven and principles-based tools is emerging. New compute hardware, productivity software, and training resources have the potential to radically accelerate progress. However, long-term support mechanisms are still necessary to sustain the momentum and maintenance of critical foundational packages.
The expected halt of traditional technology scaling is motivating increased heterogeneity in high-performance computing (HPC) systems with the emergence of numerous specialized accelerators. As heterogeneity increases, so does the risk of underutilizing expensive hardware resources if we preserve today’s rigid node configuration and reservation strategies. This has sparked interest in resource disaggregation to enable finer-grain allocation of hardware resources to applications. However, there is currently no data-driven study of what range of disaggregation is appropriate in HPC. To that end, we perform a detailed analysis of key metrics sampled in NERSC’s Cori, a production HPC system that executes a diverse open-science HPC workload. In addition, we profile a variety of deep-learning applications to represent an emerging workload. We show that for a rack (cabinet) configuration and applications similar to Cori, a central processing unit with intra-rack disaggregation has a 99.5% probability to find all resources it requires inside its rack. In addition, ideal intra-rack resource disaggregation in Cori could reduce memory and NIC resources by 5.36% to 69.01% and still satisfy the worst-case average rack utilization.
RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.
Community resilience hubs are locally identified and community-serving facilities that provide residents year-round access to support resources. During extreme weather, they can reduce the burden on emergency response teams by supplying power before, during, and after grid outages through onsite energy systems. This presentation analyzes how NREL's REopt tool can leverage energy efficiency, distributed generation, and storage resources to ensure critical community facilities are online when they are needed most. We showcase the tool's capabilities and application through a case study that focuses on achieving resilience for critical facilities in Manatee County.
Microbial metabolism is a complex, emergent system driven by the coordinated interplay of intricate and dynamic molecular processes. To elucidate cellular behavior and enable biotechnological applications, quantitative models that address the inherent complexity of metabolism have been developed from a resource allocation perspective. Here, we synthesize recent advances in coarse-grained resource allocation frameworks and their applications in understanding microbial physiology and guiding gene circuit design. Here, these frameworks reveal global regulatory constraints and predict cellular adaptation to nutrient and environmental changes. In addition, they enable the quantification of metabolic costs, the dissection of circuit–host interactions, and the development of strategies for burden mitigation. Collectively, these modeling frameworks provide a powerful platform for uncovering quantitative principles of microbial growth and engineering robust synthetic biological systems.
The goals of this project were to create a comprehensive Environmental Resiliency Plan and to increase the capacity of all Lac du Flambeau Tribal Program Managers to incorporate environmental impact thinking into the everyday management of their departments. Environmental Resiliency Planning utilized current Tribal documents, which include the Integrated Resource Management Plan (IRMP), the Lac du Flambeau Tribal Emergency Management Plan (EMP), and the Lac du Flambeau Strategic Energy Plan, as guidance throughout the process. A vulnerability assessment initiated our technical process and allowed us to identify, quantify, and prioritize (or rank) the vulnerabilities in our system. This set the stage for a reduction and resilience plan as well as providing insight for revisions of existing management plans such as the Energy and Integrated Resources Management Plans
Unconventional oil and gas from shale formations have emerged as some of the fastest growing energy resources in the United States, providing both cleaner energy to consumers and reducing the nation’s reliance on energy imports. To properly harness these important natural resources, the nanopore structure of associated shales must be fully understood, particularly under hydraulic fracturing conditions, where they are exposed to both overburden compressive and hydrostatic fluid pressures. The current study uses small-angle neutron scattering (SANS) to characterize pore structure, including porosity, pore accessibility, and pore size distribution, in the 1–100 nm regime at elevated pressures for mineralogically distinct clay- and carbonate-rich shales from the Permian Basin. Unlike typical porosity measurement techniques, SANS is uniquely capable of characterizing both open and closed porosity, allowing measurement of how pore accessibility changes with pressure and determination of the size range of accessible versus inaccessible pores. The porosity of the clay-rich shale was 7.7%, compared to 0.51% for the carbonate-rich shale. However, only 2.6% of the nanopores in the carbonate-rich shale were inaccessible to water at 8 kPSI (55.1 MPa) compared to 7.8% for the clay-rich shale. Furthermore, our analyses indicated that the closed pores fall within distinct size ranges, likely corresponding with the chemical nature of the pore host material. These results provide valuable insight into the effects of shale petrophysical properties on hydrocarbon extraction from unconventional reservoirs.
Hydrothermal treatment (HT) is an emerging technique for sustainable sewage sludge management and resource recovery. Many sludges are rich in iron (Fe) due to the common addition of Fe salts in water resource recovery facilities. To develop guidance for reaction conditions targeting nutrient recovery, this study systematically investigated the influence of HT temperature, treatment time, and sludge source on the dynamic speciation evolution of phosphorus (P) and nitrogen (N) during HT of Fe-rich sewage sludge. Complementary chemical extraction and X-ray spectroscopy analyses were conducted to characterize the treatment products. For the sludge mixture (a blend of primary and waste activated sludges), P speciation did not change significantly within 4.5 h at 125 °C HT, while soluble and labile P was converted into insoluble P over time at 175 and 225 °C HT. Strengite (FePO 4 · 2 H 2 O) preferentially formed in the hydrochars with increasing treatment temperature and/or time, whereas 125 °C HT within 1.5 h favored the formation of vivianite (Fe 3 (PO 4 ) 2 ·8H 2 O). Organic P was completely decomposed into orthophosphate when the HT temperature reached up to 175 °C. Pyrrole-N was enriched in the hydrochars. Similar reaction pathways were observed during HT of anaerobically digested sludge, though some minor differences in Fe-associated P and organic P were observed. Meanwhile, HT of the two sludges released orthophosphate and ammonia into the process waters at 175 and 225 °C, which can be recovered by a sequential process involving struvite (MgNH 4 PO 4 ·6H 2 O) precipitation and air stripping. This study provides new insights into the transformation of P and N during HT of Fe-rich sludges as well as a modular design for maximum P and N recovery from the treatment products.
The convergence of edge computing, big data analytics, and AI with traditional scientific calculations is increasingly being adopted in HPC workflows. Workflow management systems are crucial for managing and orchestrating these complex computational tasks. However, it is difficult to identify patterns within the growing population of HPC workflows. Serverless has emerged as a novel computing paradigm, offering dynamic resource allocation, quick response time, fine-grained resource management and auto-scaling. In this paper, we propose a framework to enable HPC scientific workflows on serverless. Our approach integrates a widely used traditional HPC workflow generator with an HPC serverless workflow management system to create benchmark suites of scientific workflows with diverse characteristics. These workflows can be executed on different serverless platforms. We comprehensively compare executing workflows on traditional local containers and serverless computing platforms. Our results show that serverless can reduce CPU and memory usage respectively by 78.11% and 73.92% without compromising performance.
While the pretraining of Foundation Models (FMs) for remote sensing (RS) imagery is on the rise, models remain restricted to a few hundred million parameters. Scaling models to billions of parameters has been shown to yield unprecedented benefits including emergent abilities, but requires data scaling and computing resources typically not available outside industry R&D labs. In this work, we pair high-performance computing resources including Frontier supercomputer, America's first exascale system, and high-resolution optical RS data to pretrain billion-scale FMs. Our study assesses performance of different pretrained variants of vision Transformers across image classification, semantic segmentation and object detection benchmarks, which highlight the importance of data scaling for effective model scaling. Moreover, we discuss construction of a novel TIU pretraining dataset, model initialization, with data and pretrained models intended for public release. By discussing technical challenges and details often lacking in the related literature, this work is intended to offer best practices to the geospatial community toward efficient training and benchmarking of larger FMs.
Pumped storage hydropower (PSH) is a type of hydropower technology where energy can be stored and generated by moving water between two reservoirs of differing elevations. In addition to providing 97% of the total utility-scale hydropower storage in the United States, PSH plants have operational characteristics - such as high ramp rates and the ability to provide reserves - that contribute to greater flexibility and reliability of the power grid. New PSH technologies can provide additional flexibility beyond existing, fixed-speed units. With the emergence of high levels of variable renewable energy resources (e.g., wind and solar), energy storage is expected to be crucial to the reliability and reliance of the power grid in a low-carbon future. At diurnal and longer durations, PSH plants have some of the lowest costs per unit of energy, have been proven to be reliable and efficient, are not cycle-limited, and typically have long lives, often exceeding 50 years. The work presented here focuses on a new generation of PSH: ternary PSH and quaternary PSH (together referred to as T/Q-PSH). Given recent experience in Europe, grid operators in the United States and elsewhere are increasingly focusing their attention on T/Q-PSH as a proven, financeable technology that can offer utility-scale, long-duration, fast-acting energy storage capabilities and grid services. T/Q-PSH differs from conventional PSH in that it can provide fast-response ancillary services during both generating and pumping operations. This capability together with fast mode switching times are key attributes that make T/Q-PSH technologies attractive for managing and stabilizing electricity systems with high amounts of variable renewable energy.
Emerging standards outlining desired behaviors for Distributed Energy Resources (DER), such as IEEE 1547-2018, define several device-level control functions to regulate DER power injections/consumptions in response to locally sensed grid conditions. The ability to adjust settings of aggregations of DER with standardized embedded control functionality constitutes a mechanism which can, potentially, create undesirable or deleterious effects on the power grid. The purpose of this white paper is to highlight unintended effects stemming from improperly tuned embedded control functions in Distributed Energy Resources (DER), which could be exploited by a malicious entity as a means to attack the power grid.
Building sciences and technology directly impact human health, productivity, and resource consumption (e.g., energy and critical minerals). Addressing emerging challenges in this field requires skilled building science professionals. JUMP into STEM sought to inspire the next generation of building scientists through a real-world competition that introduced participants to the field and connected them with national laboratory and industry professionals. This report highlights select challenges from past competitions which are tailored for academic and industry professionals who aim to develop or recruit multidisciplinary talent. It also includes additional guidance to support the effective replication of these challenges.
Context: This webinar featured two presentations examining quantum computing and its complex implications across the energy, water, and materials sectors. Olivier Ezratty introduced quantum computing, its anticipated applications and added value, and the hardware required to support these systems. He also discussed their energy demands and the role of the Quantum Energy Initiative in developing an interdisciplinary research field focused on these challenges. David McCollum then explored the opportunities and multisectoral challenges associated with next-generation, quantum-accelerated data centers, including their potential energy and resource impacts and the infrastructure chokepoints that could emerge. Together, the presentations emphasized the need for long-term planning and cross-cutting research collaboration as quantum computing technologies continue to develop. Presenters: Olivier Ezratty (Quantum Energy Initiative); David McCollum (Oak Ridge National Laboratory) Moderator: Patrick M. Reed (MSD CoP Facilitation Team); Gokul Iyer (Pacific Northwest National Laboratory) This webinar was held on: July 9th, 2026 from 1:00–2:30 PM EDT.
The aviation system in Canada is described as it relates to the potential applicability of tiltrotor technology. Commuter service in two corridors, the Vancouver-Victoria route on the west coast and the heavily traveled Montreal-Toronto corridor in eastern Canada, are examined. The operation of air service from the near-downtown Toronto STOLport and from the Vancouver-Victoria downtown heliport facilities is described. The emergency medical services, search and rescue, and natural resources development sectors are described with regard to the needs that tiltrotor technology could uniquely meet in these areas. The airport construction program in isolated communities of northern Quebec and possible tiltrotor service in northern regions are reviewed. The Federal and provincial governments' financial support policy regarding the aeronautical industry is to encourage the establishment and expansion of businesses in the field of aeronautics and to make possible the acquisition of new technology. This policy has implications for the tiltrotor program.
A combination of emerging mission considerations such as 'launch on schedule', resource limitations, and the development of higher power spacecraft busses has resulted in renewed interest in high power hydrogen arcjet systems with specific impulses greater than 1000 s for Earth-space orbit transfer and maneuver applications. Solar electric propulsion systems with about 10 kW of power appear to offer payload benefits at acceptable trip times. This work outlines the design and development of 10 kW hydrogen arcjet power electronics and results of arcjet integration testing. The power electronics incorporated a full bridge switching topology similar to that employed in state of the art 5 kW power electronics, and the output filter included an output current averaging inductor with an integral pulse generation winding for arcjet ignition. Phase shifted, pulse width modulation with current mode control was used to regulate the current delivered to arcjet, and a low inductance power stage minimized switching transients. Hybrid power Metal Oxide Semiconductor Field Effect Transistors were used to minimize conduction losses. Switching losses were minimized using a fast response, optically isolated, totem-pole gate drive circuit. The input bus voltage for the unit was 150 V, with a maximum output voltage of 225 V. The switching frequency of 20 kHz was a compromise between mass savings and higher efficiency. Power conversion efficiencies in excess of 0.94 were demonstrated, along with steady state load current regulation of 1 percent. The power electronics were successfully integrated with a 10 kW laboratory hydrogen arcjet, and reliable, nondestructive starts and transitions to steady state operation were demonstrated. The estimated specific mass for a flight packaged unit was 2 kg/kW.