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NASA NTRS1988

The development of a cislunar space infrastructure

The primary objective of the University of Colorado Advanced Mission Design Program is to define the characteristics and evolution of a near-Earth space infrastructure. The envisioned foundation includes a permanently manned, self-sustaining base on the lunar surface, an L1 space station, and a transportation system that anchors these elements to a low Earth orbit (LEO) station. The motivation of this project was based on the idea that a near-Earth space infrastructure is not an end but an important step in a larger plan to expand man's capabilities in space science and technology. The presence of a cislunar space infrastructure would greatly facilitate the staging of future planetary missions, as well as facilitating the full exploration of the potential for science and industry on the lunar surface. This paper will provide a sound rationale and a detailed scenario in support of the cislunar infrastructure design.

Source record↗

NASA NTRS1999

Architectural Design for a Mars Communications and Navigation Orbital Infrastructure

The planet Mars has become the focus of an intensive series of missions that span decades of time, a wide array of international agencies and an evolution from robotics to humans. The number of missions to Mars at any one time, and over a period of time, is unprecedented in the annals of space exploration. To meet the operational needs of this exploratory fleet will require the implementation of new architectural concepts for communications and navigation. To this end, NASA's Jet Propulsion Laboratory has begun to define and develop a Mars communications and navigation orbital infrastructure. This architecture will make extensive use of assets at Mars, as well as use of traditional Earth-based assets, such as the Deep Space Network, DSN. Indeed, the total system can be thought of as an extension of DSN nodes and services to the Mars in-situ region. The concept has been likened to the beginnings of an interplanetary Internet that will bring the exploration of Mars right into our living rooms. The paper will begin with a high-level overview of the concept for the Mars communications and navigation infrastructure. Next, the mission requirements will be presented. These will include the relatively near-term needs of robotic landers, rovers, ascent vehicles, balloons, airplanes, and possibly orbiting, arriving and departing spacecraft. Requirements envisioned for the human exploration of Mars will also be described. The important Mars orbit design trades on telecommunications and navigation capabilities will be summarized, and the baseline infrastructure will be described. A roadmap of NASA's plan to evolve this infrastructure over time will be shown. Finally, launch considerations and delivery to Mars will be briefly treated.

Ceasrone R. J.↗

NASA NTRS2002

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Johnston, William E.↗

NASA NTRS2002

Orbital Aggregation and Space Infrastructure Systems (OASIS)

This paper summarizes the results of a NASA lead study performed to identify synergistic opportunities and concepts between human exploration initiatives and commercialization of space. The goal of this initiative, called Orbital Aggregation & Space Infrastructure Systems (OASIS), is to develop an in-space architecture and associated concepts that provide common infrastructure for enabling a large class of space missions. The concepts include communications, navigation and power systems, propellant modules, tank farms, habitats, and in-space transportation systems using several propulsion technologies. OASIS features in-space aggregation of systems and resources in support of mission objectives. The concepts feature a high level of reusability and are supported by inexpensive launch of propellant and logistics payloads from the Earth/moon system. Industry, NASA and other users could share infrastructure costs. The anticipated benefits of synergistic utilization of space infrastructure are reduced mission costs and increased mission flexibility for future space exploration and commercialization initiatives.

Troutman, Patrick A.↗

NASA NTRS2006

A Case for Developing a Ground Based Replication of the Earth, Moon and Mars Spaceflight Infrastructure

When the systems are developed and in place to provide the services needed to operate en route and on the Lunar and Martian surfaces, an Earth based replication will need to be in place for the safety and protection of mission success. The replication will entail all aspects of the flight configuration end to end but will not include any closed loop systems. This would replicate the infrastructure from Lunar and Martian robots, manned surface excursions, through man and unmanned terrestrial bases, through the various types of communication systems and technologies, manned and un-manned space vehicles (large and small), to Earth based systems and control centers. An Earth based replicated infrastructure will enable checkout and test of new technologies, hardware, software updates and upgrades and procedures without putting humans and missions at risk. Analysis of events, what ifs and trouble resolution could be played out on the ground to remove as much risk as possible from any type of proposed change to flight operational systems. With adequate detail, it is possible that failures could be predicted with a high probability and action taken to eliminate failures. A major factor in any mission to the Moon and to Mars is the complexity of systems, interfaces, processes, their limitations, associated risks and the factor of the unknown including the development by many contractors and NASA centers. The need to be able to introduce new technologies over the life of the program requires an end to end test bed to analyze and evaluate these technologies and what will happen when they are introduced into the flight system. The ability to analyze system behaviors end to end under varying conditions would enhance safety e.g. fault tolerances. This analysis along with the ability to mine data from the development environment (e.g. test data), flight ops and modeling/simulations data would provide a level of information not currently available to operations and astronauts. In this paper we will analyze the beginnings of such a replication and what it could do in terms of reducing risk in the near term for development. We will analyze the Space Shuttle Main Engine (SSME) test lab which has to a large extent accomplished this replication for the SSME and has been highly successful in analyzing hardware and software problems and changes. The cost of replicating the flight system as proposed here could be very high if attempted as an afterthought. We will describe the initial steps for the development of a replication of this infrastructure starting with the communication infrastructure. The Constellation of Labs (CofL) under the Command, Control, Communication and Information (C3I) project for the NASA Exploration Initiative will provide the initial foundation upon which to base this replication. Simply put, there is very little margin for error in high latency situations e.g. en-route to/from Mars or in an autonomous process on the Lunar far side. Any thought out approach to reduce risk and increase safety needs to be accomplished end to end with the actual systems configuration.

Bradford, Robert N.↗

NASA NTRS2012

Space Transportation Infrastructure Supported By Propellant Depots

A space transportation infrastructure is described that utilizes propellant depot servicing platforms to support all foreseeable missions in the Earth-Moon vicinity and deep space out to Mars. The infrastructure utilizes current expendable launch vehicle (ELV) systems such as the Delta IV Heavy, Atlas V, and Falcon 9, for all crew, cargo, and propellant launches to orbit. Propellant launches are made to Low-Earth-Orbit (LEO) Depot and an Earth-Moon Lagrange Point 1 (L1) Depot to support a new reusable in-space transportation vehicles. The LEO Depot supports missions to Geosynchronous Earth Orbit (GEO) for satellite servicing and to L1 for L1 Depot missions. The L1 Depot supports Lunar, Earth-Sun L2 (ESL2), Asteroid and Mars Missions. New vehicle design concepts are presented that can be launched on current 5 meter diameter ELV systems. These new reusable vehicle concepts include a Crew Transfer Vehicle (CTV) for crew transportation between the LEO Depot, L1 Depot and missions beyond L1; a new reusable lunar lander for crew transportation between the L1 Depot and the lunar surface; and Mars orbital Depot are based on International Space Station (ISS) heritage hardware. Data provided includes the number of launches required for each mission utilizing current ELV systems (Delta IV Heavy or equivalent) and the approximate vehicle masses and propellant requirements. Also included is a discussion on affordability with ideas on technologies that could reduce the number of launches required and thoughts on how this infrastructure include competitive bidding for ELV flights and propellant services, developments of new reusable in-space vehicles and development of a multiuse infrastructure that can support many government and commercial missions simultaneously.

Smitherman, David↗

NASA NTRS2022

Cross-Cutting Flight Infrastructure Improvements on M2020

Mars2020 (M2020) was formulated as a mission that leveraged as much Mars Science Laboratory (MSL) heritage as possible, while focusing major new development efforts on the original and unique elements needed to accomplish the different mission objectives. Well publicized examples of high profile new developments include precision landing, the sampling and caching system, the specific instrument suite, improved mobility via Autonomous Navigation, and later the addition of the Ingenuity helicopter. Less well known are the refinements to the core flight infrastructure, primarily in the cross-cutting functions of Telecom, Avionics, Data Management, Communications Behaviors, and Parameter Management. These enhancements are introduced predominately via flight software, and represent increases in capability that justified their inclusion in an otherwise heritage-focused project environment.Perseverance’s cross-cutting flight infrastructure improvements fall into and across the following five categories. First is a trimming of the software footprint of infrastructure modules, in order to make room for memory demands elsewhere in the system. Second is the minimization of data volume to be downlinked, through various methods such as the incorporation of new compression options. Third is the maximization of the available downlink bandwidth for data, by curtailing content-less data (fill) and introducing an improved UHF proximity link protocol. Fourth is a reduction in vulnerabilities, through increased file system redundancy, robustness, and software process monitoring. Fifth is an increase in operations efficiency by lowering file system mount times, improving parallelism between simultaneous events, minimizing the time to recover from file system errors, streamlining the purging of obsolete data, and reducing the number of commands to service parameters by a factor of 100.Individually, none of the cross-cutting infrastructure improvements are likely to garner headlines, but collectively they appreciably improve the safety and operability of Perseverance over its predecessor. This paper will describe the improvements, their promise, and where applicable, their actual impact in operations.

Bohannon, Emily↗

NASA NTRSDate not supplied

SPHINX: An SEP Model Validation Infrastructure developed through Community Challenges and the SEP Scoreboards

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars (Whitman et al 2022). For these reasons, SEP modelers have developed a rich and diverse set of models with a wide variety of aims. Some models probe the basic physics at the heart of particle acceleration and transport. Others produce fast statistical forecasts or employ disruptive new techniques like Machine Learning with the goal to assist end users in making operational decisions. To enable a consistent and quantitative understanding of SEP model performance, a generalized, automated validation infrastructure, called SPHINX, is being developed at NASA SRAG in close collaboration with NASA CCMC, NASA M2M, NOAA SWPC, and BIRA-IASB. This infrastructure has been built up through a multi-year community challenge. Starting in 2018 at the SHINE workshop, an effort was launched through SHINE, ISWAT, and ESWW to encourage quantitative, comprehensive, and consistent validation of SEP models. This effort has defined a set of challenge SEP events with the aim of generating quantitative comparisons between forecasts and observations and a set of challenge “non-events” to assess false alarms. In 2023, these challenge lists have been extended to statistically significant numbers with a prescribed set of rules for producing forecasts and supported through the dedicated SEPVAL working meetings. The participation of the research community has allowed the infrastructure to validate all the types of outputs being produced by SEP models. In parallel, the SPHINX code is being applied to real time forecasts submitted to the SEP Scoreboards, ensuring that the validation infrastructure can interpret forecasts produced in an operational scenario and provide metrics meaningful for operations. Upon completion, SPHINX and its interactive user interface, SPHINX-Web, will be made available for public use.

space weather↗

NASA NTRSDate not supplied

Autonomous Lunar Infrastructure Outfitting

The Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS) project at NASA Ames Research Center is developing autonomous infrastructure, instrumentation, and spacecraft assembly and manufacturing capabilities for next generation exploration and science missions, with a goal to change the cost scaling of these missions relative to mission size and duration. Using a building-block approach with a 'kit of parts' composed of ultra-light, high-performance mechanical metamaterials, simplified robots leverage the period environment to achieve high levels of autonomy and reliability for in-space and surface assembly of large-scale apertures, solar-arrays, towers, habitats, and other infrastructure. Robots and structure break down into a compact form factor for launch. By leveraging economies of scale and achieving high-packing ratios, ARMADAS technology can revolutionize space missions by breaking the tyranny of the launch shroud, decreasing development times, decreasing mission costs for transformative science capability, and providing a scalable and versatile space infrastructure strategy. An ecosystem of reconfigurable infrastructure modules can be reused, repaired, expanded reconfigured to meet emergency or unforeseen needs, and reduce spare parts.

Christine Gregg↗

DOE OSTI2020

Robotic Mapping and Monitoring of Nuclear Infrastructure

Routine inspection of nuclear infrastructure is currently expensive and slow. To remedy this the Applied Research Center (ARC) at Florida International University (FIU) is developing a field robot capable of gathering valuable data quickly, safely, and cheaply. Motivation: Nuclear infrastructure should be inspected routinely to ensure early detection of problems. This process is expensive, hazardous, and slow. Objective: Develop a platform capable of surveying nuclear infrastructure autonomously. Discussion: The quality of the captured data depends on the success of every component of the robot. Good sensors, hardware, localization, data collection, and autonomy are required. Conclusion: This is a promising approach for surveying nuclear infrastructure. The captured data is rich with information and can be evaluated by both people and algorithms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Synergies Between Nuclear Security and Critical Infrastructure: National Legal and Regulatory Frameworks

Nuclear reactors and other nuclear facilities are part of a nation's critical infrastructure assets. Key cross-sector interdependencies, in relation to energy, transportation systems, communications, emergency services, water, information technologies and others, result in inevitable synergies between legal frameworks for the security of nuclear facilities and legal frameworks for the protection of critical infrastructure. The protection of nuclear facilities against sabotage and other malicious acts is paramount in ensuring energy security and thus ensuring uninterrupted energy supply. The protection of other sectors, such as uninterrupted communications, secure water supply, and others, supports a safe and secure operation of nuclear facilities. Some countries rely on broader critical infrastructure frameworks to impose security requirements on nuclear facilities, or to achieve robust cybersecurity systems. This paper will analyze the interdependencies and synergies between the legal and regulatory frameworks for critical infrastructure protection and nuclear facilities' security by comparing various national frameworks. The paper will also propose modalities to leverage the best practices and requirements from each framework towards energy security goals and stronger national nuclear security regimes.

Man, Madalina-Anca↗

DOE OSTI2025

Utilizing AI and Spatial Data to Identify & Rapidly Disseminate Energy Infrastructure Insights

GeoGov Summit Final Presentation entitled "Utilizing AI and Spatial Data to Identify & Rapidly Disseminate Energy Infrastructure Insights". Maintaining the integrity of energy infrastructure plays a critical role in ensuring energy security. Robust foundational AI models using data from federal, state, industry, and other sources can help address integrity risk management & mitigation issues as well as evaluate extended use strategies. Trusted foundational models can help with industry adoption and accelerate innovation by enhancing integrity predictions, reduce costs, and informing infrastructure build-out. Coordination, collaboration & data sharing to develop robust models to aid in: Optimizing operations; Minimizing costs; Ensuring energy security.

Advanced Infrastructure Integrity Model (AIIM)↗

DOE OSTI2023

Cutting-Edge Operations Concepts: Intelligent Infrastructure, Cooperative Driving, Signal Control, and Curbside Management

The objective of this breakout session at the NREL Mobility workshop was to examine emerging traffic operations concepts built on key detection technology such as radars, lidars, and imaging recognition - and identify challenges and paths forward to integrate into our current roadway system. The key objective were to identify the opportunities for intelligent infrastructure to support near-term safety, equity, energy, and congestion mitigation goals, while supporting longer term connected-automated vehicle objectives. In the plenary session, Eric Raamot, from the USDOT Highly Automated Safety Systems Office challenged the participants to think broadly about the roll of standards and reference architecture to provide both an accelerated rollout of intelligent infrastructure, but also a repeatable and supportable framework upon which many infrastructure owners and operators (IOOs) could utilize for their implementation purposes.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Leveraging AI and Spatial Data to Unlock Pipeline Integrity Insights: NETL’s Advanced Infrastructure Integrity Model (AIIM)

Maintaining the integrity of natural gas infrastructure plays a critical role in ensuring energy security. Robust, data-driven foundational AI models for pipeline integrity can help address risk management and mitigation issues. Trusted foundational models can help with industry adoption and accelerate innovation by enhancing integrity predictions, reduce costs, and informing infrastructure build-out. The AIIM dashboard was released in 2022 and utilizes multi-ML models for ensemble-type insights. It was expanded to include analytics on reported incidents. It was developed as an ESRI Dashboard to support data visualization & interrogation and contains pipeline data and model results.

Advanced Infrastructure Integrity Model (AIIM)↗

DOE OSTI2023

Scaffolding civic infrastructures: Examining the role of civic technoscience in public engagements with oil and gas pipelines

Oil and gas pipelines bring attention to the importance of public participation in the management of large-scale infrastructure projects. Participation transforms how communities understand benefits and risks, and can result in safer and more resilient projects. However, participation can be hindered by procedural injustices in planning processes and lack of industry transparency. Based on a survey of 103 civil society groups conducted in 2021, this paper investigates how groups mobilize technical projects and expert knowledge to overcome these. We frame these mobilizations as expressions of civic technoscience, and argue their pivotal role in building capacity for effective engagements with pipelines. To this extent, we furthermore suggest that civic technoscience is fundamental to building civic infrastructures for reforming participatory governance gaps. We conclude with recommendations for how civic technoscience can better support the intentions of civic infrastructuring by coordinating activities across coalitions, as well as by shifting the scales at which groups engage with the governance of pipelines.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Challenges in the designing, planning and deployment of hydrogen refueling infrastructure for fuel cell electric vehicles

Hydrogen can power transportation with near zero greenhouse gas emissions. With government support, early market development is now underway in several nations thanks to technological advances in fuel cell vehicles and electricity generation from renewable energy. Deploying a sustainable hydrogen refueling infrastructure faces methodological and practical challenges ranging from the creation of appropriate codes to managing the co-evolution of the refueling network and growth of the stock of hydrogen fuel cell vehicles. Furthermore, this paper presents a comprehensive review of the challenges facing the designing, planning and deployment of hydrogen refueling infrastructure progress to date and outlook for the future. The design and costs of refueling infrastructure as well as the lifecycle environmental effects of hydrogen vehicles depend on how hydrogen is produced and delivered to refueling stations. In recent years, important advances have been made in methods for planning the numbers, sizes and location of hydrogen stations. Institutional barriers are also gradually being overcome. Co-evolving the deployment of stations and the demand for fuel cell vehicles remains a crucial subject for future research.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Future energy infrastructure, energy platform and energy storage

Today fossil energy dominates energy consumption across the world. There has been an increasing momentum to reduce fossil energy consumption and increase renewable energy utilization to more than 70%. Such high penetrations of distributed renewable resources bring large uncertainty and complexity that cannot be easily handled by the current infrastructure. For the last two decades, telecommunication industry has gone through a similar transition from centralized to distributed systems, and more recently to platform approaches, which become the corner stone of today’s vibrant platform economy. Based on telecommunication history, we believe that a platform-based approach, called the energy platform, is a viable solution for addressing the renewable energy challenges. The energy platform consists of an array of computational algorithms, sensing and control technologies for key industry, energy generators and users to jointly manage and control the complex energy infrastructure. It includes the following key components: (1) the hardware and software to generate, store, control and transmit electricity/data (the energy cloud), (2) the digital platforms and tools for key energy producers, digital, service and communication industry to share the assets, participate in and manage the complex infrastructure, and for customers to participate in energy transactions, (3) the transaction platform for new service and business models. Additionally, the energy platform requires breakthroughs in large scale energy storage and many other areas including efficient power electronics, sensors and controls, new mathematical and computational tools, and deep integration of energy technologies and information sciences to control and stabilize such complex chaotic systems.

25 ENERGY STORAGE↗

DOE OSTI2020

Series of semi-Markov processes to model infrastructure resilience under multihazards

Civil infrastructure systems are subjected to multiple hazards, including natural and anthropogenic, that disrupt their function or the level of service offered. Estimating the function recovery of these systems (or how soon normalcy of operations will be restored) when subjected to repeated hazard events by considering the inter-event dependencies is an important problem in multihazard infrastructure resilience. However, this problem has been less addressed in the field. This paper proposes a series of semi-Markov processes model to capture the inter-event dependencies in infrastructure recovery when subjected to successive hazard events. Recovery after each new hazard event is represented by a unique semi-Markov process that models the reduced recovery rates and the increased recovery times caused by the system’s incomplete recovery from the preceding event. Two novel formulations of the inter-event dependency modeling, namely Maximal Effects Dependency (considers the worst impact of two successive hazard events) and Cumulative Effects Dependency (considers the aggregated impacts of two successive hazard events), are proposed and discussed. The model is demonstrated by considering the following applications: Three-state system subjected to deterministic and random occurrences of identical hazard events; and Multihazard resilience of a building in Charleston, SC, considering earthquake and hurricane hazards. Results indicate that considering inter-event dependencies in recovery modeling can lead to lesser-predicted resilience, thereby affecting resilience-based decision-making.

42 ENGINEERING↗