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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Federation in genomics pipelines: techniques and challenges

Federation is a popular concept in building distributed cyberinfrastructures, whereby computational resources are provided by multiple organizations through a unified portal, decreasing the complexity of moving data back and forth among multiple organizations. Federation has been used in bioinformatics only to a limited extent, namely, federation of datastores, e.g. SBGrid Consortium for structural biology and Gene Expression Omnibus (GEO) for functional genomics. Here, we posit that it is critical to federate both computational resources (CPU, GPU, FPGA, etc.) and datastores to support popular bioinformatics portals, with fast-increasing data volumes and increasing processing requirements. A prime example, and one that we discuss here, is in genomics and metagenomics. It is vital that the processing of the data be done without having to transport the data across large network distances. We exemplify our design and development through our experience with metagenomics-RAST (MG-RAST), the most popular metagenomics analysis pipeline. Currently, it is hosted completely at Argonne National Laboratory. Yet, through a recently started collaborative National Institutes of Health project, we are taking steps toward federating this infrastructure. Being a widely used resource, we have to move toward federation without disrupting 50 K annual users. Here, we describe the computational tools that will be useful for federating a bioinformatics infrastructure and the open research challenges that we see in federating such infrastructures. It is hoped that our manuscript can serve to spur greater federation of bioinformatics infrastructures by showing the steps involved, and thus, allow them to scale to support larger user bases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Methods and Experiences for Developing Abstractions for Data-intensive, Scientific Applications

Developing software for scientific applications that require the integration of diverse types of computing, instruments, and data present challenges that are distinct from commercial software. These applications require scale, and the need to integrate various programming and computational models with evolving and heterogeneous infrastructure. Pervasive and effective abstractions for distributed infrastructures are thus critical; however, the process of developing abstractions for scientific applications and infrastructures is not well understood. While theory-based approaches for system development are suited for well-defined, closed environments, they have severe limitations for designing abstractions for scientific systems and applications. The design science research (DSR) method provides the basis for designing practical systems that can handle real-world complexities at all levels. In contrast to theory-centric approaches, DSR emphasizes both practical relevance and knowledge creation by building and rigorously evaluating all artifacts. In this work, we show how DSR provides a well-defined framework for developing abstractions and middleware systems for distributed systems. Specifically, we address the critical problem of distributed resource management on heterogeneous infrastructure over a dynamic range of scales, a challenge that currently limits many scientific applications. We use the pilot-abstraction, a widely used resource management abstraction for high-performance, high throughput, big data, and streaming applications, as a case study for evaluating the DSR activities. For this purpose, we analyze the research process and artifacts produced during the design and evaluation of the pilot-abstraction. We find DSR provides a concise framework for iteratively designing and evaluating systems. Finally, we capture our experiences and formulate different lessons learned.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The SENSEI Generic In Situ Interface

The SENSEI generic in situ interface is an API that promotes code portability and reusability. From the simulation view, a developer can instrument their code with the SENSEI API and then make make use of any number of in situ infrastructures. From the method view, a developer can write an in situ method using the SENSEI API, then expect it to run in any number of in situ infrastructures, or be invoked directly from a simulation code, with little or no modification. This paper presents the design principles underlying the SENSEI generic interface, along with some simplified coding examples.

Ayachit, Utkarsh↗
DOE OSTI2023

A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation

As the use of combustion engine vehicles plays a deciding role in global warming, we can observe a trend to replace them with electric vehicles (EV) driven by new environmentally conscious policies and increasing technological capabilities. With improvements in driving range and reduction in prices come new challenges that may hamper the progress towards complete battery driven transportation. A major challenge for the increasing EV adoption is the planning of extensions to existing infrastructure or the inclusion of new infrastructure components in the planning process. This demands increasingly complex planning tools that can simulate the interplay between different stakeholders in modern transportation scenarios such as EVs, charging stations, energy providers, and general transportation participants. Simulation platforms for agent-based modeling in transportation have been developed as effective interactive tools that allow planners to explore different trade-offs across different scenarios with the ability to simulate the impact of policy or infrastructure decisions on the different stakeholders in the simulation. This article surveys several of the major simulation platforms that include modern EV-based forms of transportation and allow the simulation of relevant infrastructure components alongside the well established transportation simulations. These tools allow researchers to analyze expected traffic flow, identify possible charging station locations based on area demand, predict electrical grid demand, and more. Here this survey intends to make it easier for researchers to identify and apply a simulation platform in the context of supporting the increasing electrification of the transportation sector, enabling more efficient simulation and planning capabilities in this domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Visualizing Comparisons of Bill of Materials

Protecting critical infrastructure from cyber attacks, natural disasters, and other disruptions is a priority of the U.S. Government. Critical infrastructure includes providing electricity to homes and businesses, supplying natural gas for heating, and producing renewable energy sources. A loss of these services, as seen in the Solarwinds supply chain attack in 2020 , Texas snowstorm of 2021, the Colonial Pipeline cyber incident of 2021, and the Washington power substation attacks in 2022 result in high costs to consumers, disruption of everyday life, and even death. To protect the infrastructure, we first have to know what equipment we are protecting. The complexity of distributed manufacturing and development coupled with the increasing prevalence of cyber and supply chain attacks necessitates a greater understanding of the hardware and software components that comprise equipment in critical infrastructure. When a vulnerability in a single software library can have disastrous consequences, it is vital to understand critical equipment and systems at a granular level. This need has led to increased energy around the development and incorporation of bill-of-materials (BOM) into existing asset management practices to aid in mitigating, and responding to future attacks \cite{noauthor_software_nodate}. While much of the current research is devoted to creating BOMs, it is equally important to develop methodologies for leveraging BOMs to answer questions, such as: How has my software changed? Are two pieces of equipment equivalent? Does this piece of equipment that just arrived match my historical information? In this work, we demonstrate how BOMs can be represented by graph structures. We then describe how these structures can be fed into a graph comparison algorithm to produce a novel interactive visualization that allows us to not only identify differences in BOMs, but show exactly where they are in the product.

Jones, Rebecca D.↗
DOE OSTI2018

Guidelines and considerations for designing field experiments simulating precipitation extremes in forest ecosystems

1. Precipitation regimes are changing in response to climate change, yet understanding of how forest ecosystems respond to extreme droughts and pluvials remains incomplete. As future precipitation extremes will likely fall outside the range of historical variability, precipitation manipulation experiments (PMEs) are critical to advancing knowledge about potential ecosystem responses. However, few PMEs have been conducted in forests compared to short-statured ecosystems, and forest PMEs have unique design requirements and constraints. Moreover, past forest PMEs have lacked coordination, limiting cross-site comparisons. Here, we review and synthesize approaches, challenges, and opportunities for conducting PMEs in forests, with the goal of guiding design decisions, while maximizing the potential for coordination. 2. We reviewed 63 forest PMEs at 70 sites world-wide. Workshops, meetings, and communications with experimentalists were used to generate and build consensus around approaches for addressing the key challenges and enhancing coordination. 3. Past forest PMEs employed a variety of study designs related to treatment level, replication, plot and infrastructure characteristics, and measurement approaches.Important considerations for establishing new forest PMEs include: selecting appropriate treatment levels to reach ecological thresholds; balancing cost, logistical complexity, and effectiveness in infrastructure design; and preventing unintended water subsidies. Response variables in forest PMEs were organized into three broad tiers reflecting increasing complexity and resource intensiveness, with the first tier representing a recommended core set of common measurements. 4. Differences in site conditions combined with unique research questions of experimentalists necessitate careful adaptation of guidelines for forest PMEs to balance local objectives with coordination among experiments. We advocate adoption of a common framework for coordinating forest PME design to enhance cross-site comparability and advance fundamental knowledge about the response and sensitivity of diverse forest ecosystems to precipitation extremes.

Climate Extremes, drought, ecological thresholds, ↗
DOE OSTI2024

Investigating In-Situ Fracture Behaviors of Polymer Pipeline Materials in Hydrogen and Hydrogen-Methane Blended Gas Environments

To reduce carbon emissions, the US natural gas infrastructure is seen as a primary solution for efficiently transporting hydrogen gas. Blending hydrogen gas with natural gas and transporting it across a national infrastructure could save significant infrastructure costs. To properly operate the infrastructure under the new gas system, it is critical to understand material compatibility with hydrogen under various conditions. The Blended Gas CRADA, a Hyblend project, is established to determine the material compatibility of existing natural gas pipes with hydrogen gas. In this study, we investigate the in-plane fracture behaviors of MDPEMarlex and HDPEGDB exposed to hydrogen and hydrogen-methane blended gas. Single-edge notch bending geometry is used. All tests are executed in-situ with the gas environment. The experimental results show a significant effect of the gas environment on HDPEGDB specimens, reducing 5% (H2) to 42% (Blended gas) of specific fracture energy compared to non-aged specimens. For the MDPEMarlex, the effects of the gas environment have increased the specific fracture energy by 10% (H2) to 15% (Blended gas). Fracture surfaces of the tested samples are observed using an electronic microscope. The in-plane fracture surface of HDPEGDB shows a pronounced dimple fracture pattern after exposure to hydrogen and blended gas. The expanded fracture pattern contributes to lower the specific fracture energy. These observations provide critical information for validating polymer pipeline materials when interact with hydrogen and hydrogen-blend gas.

Ko, Seunghyun↗
DOE OSTI2022

Fiber-optic sensor packaging assessment and benchmarking for embedded sensing applications

Fiber optic-based sensing for non-destructive evaluation (NDE) and structural health monitoring of various infrastructure and energy assets is an increasingly important sensing scheme. Because of their immunity to electromagnetic interferences, versatility in sensing mechanisms and designs as well as capability for distributed sensing, the fiber optic sensing is of great interest for embedding within infrastructures using advanced manufacturing methods. However, the protection of fiber optic sensors during advanced manufacturing-based embedding is an important aspect for infrastructure monitoring in practice. While successful installation of fiber optic sensors has been accomplished through application of epoxy or adhesives on infrastructure surfaces, there has been only limited investigation of fiber protection packaging schemes which are compatible with in-situ repair techniques such as the metallic cold-spray. With increasing interest and importance of cold spray-based repair processes, the integration of fiber optic sensors simultaneously during the repair is equally important. In this work, we focus our efforts on investigating various types of packaging schemes for their compatibility and integrability on the surfaces of metallic structures such as oil and gas pipelines during an in-situ repair coating. First, we consider sandblasting using silica sand particles of various size for optical fibers on the surface of a metallic coupon as a useful proxy test of sensor packaging stability. Structural damage of packaging is characterized by means of optical microscopy and the optical integrity of embedded fiber optic cables is examined using optical backscatter reflectometry (OBR). In addition, initial investigation of metallic cold-spray embedded fiber optic cables under various packaging on metallic substrates is also considered with early conclusions and future directions.

Fiber-optic sensors, Sensors packaging, Metallic C↗
DOE OSTI2022

Essential Function Analysis Capability

The Essential Function Analysis Capability (EFAC) is an extension of the All Hazards Knowledge Framework (AHA) and is a dynamic analytical framework that enables critical infrastructure knowledge discovery and decision support across the five mission areas – prevention, protection, mitigation, response and recovery. EFAC provides the ability to store and model infrastructure systems as a linked multigraphs providing an intuitive and natural representation. These infrastructure systems can then be tied to the organizational and essential function breakdown of an entity. This capability provides the foundation to rapidly evaluate and understand the potential consequences of manmade and natural disaster on these infrastructure systems and essential functions.

Hoover, MichaelJ.↗
DOE OSTI2019

Understanding Future Safety of Dams in a Changing Climate

The safety of critical water infrastructures such as dams that are upstream of population centers and aging is gaining attention due to rapid change to landscape, climate and society. In general, Probable Maximum Precipitation (PMP) is used in the design to ensure public safety of such critical water infrastructures. We demonstrate an approach where PMP can be derived from combining traditional engineering practice and modern climate science. Using the US Pacific Northwest as an example, PMP was computed from an ensemble of earth system models and verified against historical values already used in the design of the aging water infrastructures. Our engineering-climate science approach indicates that PMP in the PNW is likely to increase by 2099 significantly compared to current estimates under a climate change scenario (RCP 8.5), mandating the need for a reevaluation of safety and resilience of these critical infrastructure now rather than later, at least in the US Pacific Northwest.

Chen, Xiaodong↗
DOE OSTI2023

Limited Role of Absolute Humidity in Intraurban Heat Variability

Abstract Monitoring and understanding the variability of heat within cities is important for urban planning and public health, and the number of studies measuring intraurban temperature variability is growing. Recognizing that the physiological effects of heat depend on humidity as well as temperature, measurement campaigns have included measurements of relative humidity alongside temperature. However, the role the spatial structure in humidity, independent from temperature, plays in intraurban heat variability is unknown. Here we use summer temperature and humidity from networks of stationary sensors in multiple cities in the United States to show spatial variations in the absolute humidity within these cities are weak. This variability in absolute humidity plays an insignificant role in the spatial variability of the heat index and humidity index (humidex), and the spatial variability of the heat metrics is dominated by temperature variability. Thus, results from previous studies that considered only intraurban variability in temperature will carry over to intraurban heat variability. Also, this suggests increases in humidity from green infrastructure interventions designed to reduce temperature will be minimal. In addition, a network of sensors that only measures temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location, allowing for lower-cost heat monitoring networks. Significance Statement Monitoring the variability of heat within cities is important for urban planning and public health. While the physiological effects of heat depend on temperature and humidity, it is shown that there are only weak spatial variations in the absolute humidity within nine U.S. cities, and the spatial variability of heat metrics is dominated by temperature variability. This suggests increases in humidity will be minimal resulting from green infrastructure interventions designed to reduce temperature. It also means a network of sensors that only measure temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location.

Meteorology & Atmospheric Sciences↗
DOE OSTI2016

A hybrid computational strategy to address WGS variant analysis in >5000 samples

Abstract Background The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS environment and supercomputers also have limitations due to which large scale joint variant calling becomes infeasible, and infrastructure specific variant calling strategies either fail to scale up to large datasets or abandon joint calling strategies. Results We present a high throughput framework including multiple variant callers for single nucleotide variant (SNV) calling, which leverages hybrid computing infrastructure consisting of cloud AWS, supercomputers and local high performance computing infrastructures. We present a novel binning approach for large scale joint variant calling and imputation which can scale up to over 10,000 samples while producing SNV callsets with high sensitivity and specificity. As a proof of principle, we present results of analysis on Cohorts for Heart And Aging Research in Genomic Epidemiology (CHARGE) WGS freeze 3 dataset in which joint calling, imputation and phasing of over 5300 whole genome samples was produced in under 6 weeks using four state-of-the-art callers. The callers used were SNPTools, GATK-HaplotypeCaller, GATK-UnifiedGenotyper and GotCloud. We used Amazon AWS, a 4000-core in-house cluster at Baylor College of Medicine, IBM power PC Blue BioU at Rice and Rhea at Oak Ridge National Laboratory (ORNL) for the computation. AWS was used for joint calling of 180 TB of BAM files, and ORNL and Rice supercomputers were used for the imputation and phasing step. All other steps were carried out on the local compute cluster. The entire operation used 5.2 million core hours and only transferred a total of 6 TB of data across the platforms. Conclusions Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low coverage data can be accomplished in a scalable, cost effective and fast manner by using heterogeneous computing platforms without compromising on the quality of variants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Oilwell Conversion (Well API 121913310501) to Geothermal Heat Storage Well for Flexible Electricity Storage

Geothermal growth is limited by a lack of geographically dispersed high-temperature thermal resources and high initial upfront investment in characterization and well construction. This project intended to address the challenges of energy supply intermittency and enhance grid resilience, reliability, and energy security by storing energy provided from currently available renewable resources in the subsurface to harvest it a later time during at-peak energy demand. This project intended to improve geothermal adoption, reduce initial project risk, and improve price competitiveness through utilizing existing oil and gas infrastructure such as non-productive wells, non-economic fields, dry holes, and orphaned wells. The project also intended to address the lack of geographically dispersed thermal resources and enhance grid resilience, reliability, and energy security by introducing an economical method for storing energy from currently available renewable resources in the subsurface for usage during at-peak energy demand. During this research, the project furthered the understanding of the feasibility of utilizing abandoned oil and gas wells as geothermal heat storage wells. The project team investigated the heat storage and hydrogeological characteristics of subsurface reservoirs in the Illinois Basin to evaluate their response to heat injection for determining the evolution of temperature profiles and heat losses over time using existing and available data sets. The project team then performed modeling and simulation to evaluate the heat losses of returning fluids during heat extraction. The outputs were used to select an optimal candidate reservoir and location in Southern Illinois. The team designed and performed a small-scale field test in an existing oil well to refine the model and to demonstrate the permitting and regulatory pathways necessary for the conversion of oil and gas assets to geothermal use. The field test also serves as a proof of concept and can guide the procedures for future research and implementation. Additionally, the project team, conducted initial market research and customer discovery to develop a go to market strategy for an Advanced Geothermal Energy Storage (AGES) system. The project team in this research also identified the parameters to be refined in future research, to improve the current go to market strategy economic model. To this end several subject matter experts were also identified to assist in future research with geothermal infrastructure setup, energy storage policy and law, energy storage market demand, potential siting based on demand etc. Future research will involve further sophistication of the site commercial modeling, implementing a larger-scale test, and further refinement of the thermodynamic modeling/simulation process. The output will be lifecycle costs and economics suitable for comparison to alternative approaches from a validated full-scale demonstration for venture capital investment into this technology. The project successfully demonstrated the ability to leverage existing oilfield infrastructure, permits, and land access and leasing agreements, to enable geothermal storage projects to come online faster and cheaper than a greenfield development could. This technology could allow for greater energy independence and security through long-term energy storage solutions. The longer duration allows for greater storage for renewables currently limited by hours-long storage durations of lithium-ion. The AGES system would support the growth of renewable energy farms, and provide greater opportunities for a cleaner energy infrastructure.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Energy-Community-Geo-Database

Fundamental to understanding evolving infrastructure and technology is understanding the drivers for energy communities that affect where and how infrastructure is placed and used. An Energy Community Geo Database aligned to carbon storage systems will aid stakeholders in decision making around key future infrastructure (e.g., CCS injection locations) placement while helping contextualize these analyses against past and present-day social and environmental attributes. Much of the data required to support analyses are available from authoritative, largely governmental sources, but at present are disparate and require time-consuming acquisition, integration, and upkeep for currency. The CCS-EC-GB v2.0 integrates datasets from various federal agencies and authoritative sources to aid stakeholders and decision makers of the social and environmental factors that might impact the viability of CCS and energy related project implementation. There are 5 categories in the CCS-EC-GB v2 database. Most of the layers within each category have been updated in this version. As compared to the old database, there is 1 new category in the CCS-EC-GB v2 database: infrastructure. This is an evolving project and application will be updated periodically with new datasets and information. Notes for consideration: This database/web map will be updated with additional as new data and information becomes available and has been processed, reviewed, and approved for release. Additional state and federal entity data are planned to be integrated and included in future revisions. Summary layers provided in this application are derived from proprietary layers and do not always contain key features (age, status, or TVD) and therefore might not be shown when data are queried for those features.

CCS,Carbon capture and storage,Carbon storage,U.S.↗
DOE OSTI2017

AIMES Final Technical Report

Many important advances in science and engineering are due to large-scale distributed computing. Notwithstanding this reliance, we are still learning how to design and deploy large-scale production Distributed Computing Infrastructures (DCI). The AIMES project was conceived against this backdrop, following on the heels of a comprehensive survey of scienti c distributed applications [1]. The survey established, arguably for the rst time, the relationship between infrastructure and scienti c distributed applications. It examined well known contributors to the complexity associated with infrastructure, such as inconsistent internal and external interfaces, and demonstrated the correlation with application brittleness. It discussed how infrastructure complexity reinforces the challenges inherent in developing distributed applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Review of Data Landscape: Challenges and Opportunities

Traditional (macro-) economic impact analysis has a role in the long-run analysis of the effects of changes in resilience, since in the long-run the economy adjusts to the microeconomic impacts through various mechanisms (Kunreuther & Roth, 1998). However, measures of economic health, growth, or expansion are not sufficient for measuring resilience. The majority of infrastructure in the United States is privately owned and operated or is managed through some private-public arrangement. Most effects from changes in resilience should be assessed through short-run microeconomic analysis since the actions of firms will be spurred by internal economic decisionmaking that will have immediate impacts on local economies. Any forthcoming efforts to include resilience in the economic impacts of long duration EP outages must accommodate the private and simultaneously public nature of the EP infrastructure as well as its role as lifeline infrastructure. Resilience metrics and methodologies will only be helpful to stakeholders if these metrics help them understand the value of improvements to the resilience of communities, infrastructures, or industries. In their paper, Schellenberg et al. (2018) have provided a well thought out "lay of the lane of the common methods of estimating the economic costs of EP disruptions, which includes discussion of the difference between costs of outage and regional economic modeling, strengths and weaknesses of methods, the difficulty in incorporating resilience, data collection and availability issues, and recommendations for future research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Check the Stack: An Enabling Framework for Resilient Microgrids

Highly destructive natural disasters have illustrated the fragility of critical infrastructure including emergency services, healthcare, and water treatment during long-term electricity outages. One pathway to increase the resilience of critical infrastructure amidst disruptions to grid systems is developing microgrids, particularly those that incorporate solar photovoltaics (PV) and energy storage. This document defines a resilient microgrid as a set of interconnected load that includes critical infrastructure and distributed energy resources with the ability to island from the grid during an outage. Research is limited with respect to how much critical infrastructure could benefit from microgrids, how many states have pursued this prioritization approach, and what policies need to be in place to support more widespread deployment. This report explores each of these questions to offer the industry and policymakers a clearer understanding of the opportunity for resilient microgrids and how policy can be designed to support this market.

14 SOLAR ENERGY↗
DOE OSTI2018

2014-2018 Summary of NCAR activities in the Earth Energy Exascale System Model (E3SM) project

NCAR participation in E3SM activities as part of this funded collaborative project has been successful in leveraging the existing atmosphere model development experience from CESM scientists and applying it to initial v1 atmosphere model (EAM) development and analysis. NCAR partners collectively had many decades of experience in parameterization development, running and tuning coupled models and building the required software infrastructure to support ongoing model developments. Furthermore, collaboration between E3SM and CESM developers was of mutual benefit to both modeling endeavors. In the earlier periods of the project, participation in E3SM both complemented core critical path DOE activities and advanced individual parameterization development; including orographic drag, convection parameterization, convective gustiness and cloud and microphysical processes. Significant progress has been made implementing model capabilities for separating out the physics and dynamics grids, and providing the infrastructure for including orographic elevation class communication between the land and atmosphere models. Our activities working with the E3SM workflow and software engineering teams have established efficient protocols and infrastructure for the sharing of CESM and E3SM model codes of interest to both modeling groups, a large component of which is the mutual communication of common code bugs. As well as these specific project tasks all NCAR project members have been regular participants in atmosphere and coupled group telecons, as well as PI meetings. We have been fully engaged with and contributed to decisions regarding v1 atmosphere model developments, coupled model simulations, model tunings, and software engineering infrastructure. NCAR’s contribution to more recent E3SM development activities has centered on analysis of v1 release and pre-release simulations in order to address outstanding systematic biases and communicate climate improvements. Of particularly note is the work in understanding clouds and cloud feedbacks, shortcomings in ENSO and sub-seasonal variability; in particular the Madden Julian Oscillation (MJO). Contributions have been made to a number of papers that are currently published or in preparation detailing model performance in CMIP6-protocal experiments. They outline the simulations of mean climate, clouds and convection processes, convective gustiness, atmospheric blocking coupled climates. The contributions of NCAR’s funded activities to the E3SM atmosphere in the initial years of the project have had a positive impact on many aspects of the model simulations described in these papers.

58 GEOSCIENCES↗