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DOE OSTI2014

Department of Energy's Biological and Environmental Research Strategic Data Roadmap for Earth System Science

Rapid advances in experimental, sensor, and computational technologies and techniques are driving exponential growth in the volume, acquisition rate, variety, and complexity of scientific data. This wealth of scientifically meaningful data has tremendous potential to lead to scientific discovery. However, to achieve scientific breakthroughs, these data must be exploitable—they must be analyzed effectively and efficiently and the results shared and communicated easily within the wider Department of Energy’s (DOE’s) Biological and Environmental Research (BER) Climate and Environmental Sciences Division (CESD) community. The explosion in data complexity and scale makes these tasks exceedingly difficult to achieve, particularly given that an increasing number of disciplines are working across techniques, integrating simulation and experimental or observational results (see Table 5 in Appendix 2). Consequently, we need new approaches to data management, analysis, and visualization that provide research teams with easy-to-use and scalable end-to-end solutions. These solutions must facilitate (and where feasible, automate and capture) every stage in the data lifecycle (shown in Figure 1), from collection to management, annotation, sharing, discovery, analysis, and visualization. In addition, the core functionalities are the same across climate science communities, but they require customization to adapt to specific needs and fit into research and analysis workflows. To this end, the mission of CESD’s Data and Informatics Program is to integrate all existing and future distributed CESD data holdings into a seamless and unified environment for the acceleration of Earth system science.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Commercial and Multifamily Building Tenant Energy Usage Aggregation and Privacy

In a number of cities and states, building owners are required to disclose and/or benchmark their building energy use. This requires the building owner to possess monthly whole-building energy usage information, which can be challenging for buildings in which individual tenants have their own utility meters and accounts with the utility. Some utilities and utility regulators have turned to aggregation of customer data as a way to give building owners the whole-building energy usage data while protecting customer privacy. However, no utilities or regulators appear to have conducted a concerted statistical, cybersecurity, and privacy analysis to justify the level of aggregation selected. Therefore, the Tennant Data Aggregation Task was established to help utilities address these issues and provide recommendations as well as a theoretical justification of the aggregation threshold. This study is focused on the use case of submitting data for ENERGY STAR Portfolio Manager (ESPM), but it also looks at other potential use cases for monthly energy consumption data.

data aggergation↗

DOE OSTI2015

Design Concepts for an Outage Control Center Information Dashboard

The nuclear industry, and the business world in general, is facing a rapidly increasing amount of data to be dealt with on a daily basis. In the last two decades, the steady improvement of data storage devices and means to create and collect data along the way influenced the manner in which we deal with information. Most data is still stored without filtering and refinement for later use. Many functions at a nuclear power plant generate vast amounts of data, with scheduled and unscheduled outages being a prime example of a source of some of the most complex data sets at the plant. To make matters worse, modern information and communications technology is making it possible to collect and store data faster than our ability to use it for making decisions. However, in most applications, especially outages, raw data has no value in itself; instead, managers, engineers and other specialists want to extract the information contained in it. The complexity and sheer volume of data could lead to information overload, resulting in getting lost in data that may be irrelevant to the task at hand, processed in an inappropriate way, or presented in an ineffective way. To prevent information overload, many data sources are ignored so production opportunities are lost because utilities lack the ability to deal with the enormous data volumes properly. Decision-makers are often confronted with large amounts of disparate, conflicting and dynamic information, which are available from multiple heterogeneous sources. Information and communication technologies alone will not solve this problem. Utilities need effective methods to exploit and use the hidden opportunities and knowledge residing in unexplored data resources. Superior performance before, during and after outages depends upon the right information being available at the right time to the right people. Acquisition of raw data is the easy part; instead, it is the ability to use advanced analytical, data processing and data visualization methods to turn the data into reliable information and comprehensible, actionable information. Techniques like data mining, filtering and analysis only work reliably for well-defined and well-understood problems. The path from data to decision is more complex. The ability to communicate knowledge during outages and emergent issues is crucial. This paper presents an approach to turn the unused data into an opportunity: applying principles from semiotics, human factors and visual analytics to transform the traditional way of processing outage data into media that will improve the collective situation awareness, knowledge, decisions, actions and overall performance of the entire outage team, and also support the reliability, quality and overall effectiveness of maintenance work. The application of the proposed visualization methods will become the medium of a semi-automated analytical process where humans and machines cooperate using their respective, distinct capabilities for the most effective results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software for Depletion and Fuel Management

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the software release referred to as ADDER v1.1.0. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software for Depletion and Fuel Management

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 ( https://www.nfdi4health.de/task-force-covid-19-2 ) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

60 APPLIED LIFE SCIENCES↗

NASA NTRS1985

A performance measurement system for engineering services

A performance measurement system which provides both a means of monitoring performance and a resource to support management decision making is described. The process of performance indicator development is discussed and typical indicators are described. The paper concludes with a summary of some of the lessons learned in applying productivity measurements to engineering services tasks and in automating data collection, evaluation and interpretation.

West, R. L.↗

NASA NTRS1991

Object oriented development of engineering software using CLIPS

Engineering applications involve numeric complexity and manipulations of a large amount of data. Traditionally, numeric computation has been the concern in developing an engineering software. As engineering application software became larger and more complex, management of resources such as data, rather than the numeric complexity, has become the major software design problem. Object oriented design and implementation methodologies can improve the reliability, flexibility, and maintainability of the resulting software; however, some tasks are better solved with the traditional procedural paradigm. The C Language Integrated Production System (CLIPS), with deffunction and defgeneric constructs, supports the procedural paradigm. The natural blending of object oriented and procedural paradigms has been cited as the reason for the popularity of the C++ language. The CLIPS Object Oriented Language's (COOL) object oriented features are more versatile than C++'s. A software design methodology based on object oriented and procedural approaches appropriate for engineering software, and to be implemented in CLIPS was outlined. A method for sensor placement for Space Station Freedom is being implemented in COOL as a sample problem.

Yoon, C. John↗

NASA NTRS1994

HLLV avionics requirements study and electronic filing system database development

This final report provides a summary of achievements and activities performed under Contract NAS8-39215. The contract's objective was to explore a new way of delivering, storing, accessing, and archiving study products and information and to define top level system requirements for Heavy Lift Launch Vehicle (HLLV) avionics that incorporate Vehicle Health Management (VHM). This report includes technical objectives, methods, assumptions, recommendations, sample data, and issues as specified by DPD No. 772, DR-3. The report is organized into two major subsections, one specific to each of the two tasks defined in the Statement of Work: the Index Database Task and the HLLV Avionics Requirements Task. The Index Database Task resulted in the selection and modification of a commercial database software tool to contain the data developed during the HLLV Avionics Requirements Task. All summary information is addressed within each task's section.

Source record↗

NASA NTRS1998

Human-Centered Design of Human-Computer-Human Dialogs in Aerospace Systems

A series of ongoing research programs at Georgia Tech established a need for a simulation support tool for aircraft computer-based aids. This led to the design and development of the Georgia Tech Electronic Flight Instrument Research Tool (GT-EFIRT). GT-EFIRT is a part-task flight simulator specifically designed to study aircraft display design and single pilot interaction. ne simulator, using commercially available graphics and Unix workstations, replicates to a high level of fidelity the Electronic Flight Instrument Systems (EFIS), Flight Management Computer (FMC) and Auto Flight Director System (AFDS) of the Boeing 757/767 aircraft. The simulator can be configured to present information using conventional looking B757n67 displays or next generation Primary Flight Displays (PFD) such as found on the Beech Starship and MD-11.

Mitchell, Christine M.↗

NASA NTRS1999

Information Flow in the Launch Vehicle Design/Analysis Process

This paper describes the results of a team effort aimed at defining the information flow between disciplines at the Marshall Space Flight Center (MSFC) engaged in the design of space launch vehicles. The information flow is modeled at a first level and is described using three types of templates: an N x N diagram, discipline flow diagrams, and discipline task descriptions. It is intended to provide engineers with an understanding of the connections between what they do and where it fits in the overall design process of the project. It is also intended to provide design managers with a better understanding of information flow in the launch vehicle design cycle.

Humphries, W. R., Sr.↗

NASA NTRS2009

Human Research Program Integrated Research Plan

The Integrated Research Plan (IRP) describes the portfolio of Human Research Program (HRP) research and technology tasks. The IRP is the HRP strategic and tactical plan for research necessary to meet HRP requirements. The need to produce an IRP is established in HRP-47052, Human Research Program - Program Plan, and is under configuration management control of the Human Research Program Control Board (HRPCB). Crew health and performance is critical to successful human exploration beyond low Earth orbit. The Human Research Program (HRP) is essential to enabling extended periods of space exploration because it provides knowledge and tools to mitigate risks to human health and performance. Risks include physiological and behavioral effects from radiation and hypogravity environments, as well as unique challenges in medical support, human factors, and behavioral or psychological factors. The Human Research Program (HRP) delivers human health and performance countermeasures, knowledge, technologies and tools to enable safe, reliable, and productive human space exploration. Without HRP results, NASA will face unknown and unacceptable risks for mission success and post-mission crew health. This Integrated Research Plan (IRP) describes HRP s approach and research activities that are intended to address the needs of human space exploration and serve HRP customers and how they are integrated to provide a risk mitigation tool. The scope of the IRP is limited to the activities that can be conducted with the resources available to the HRP; it does not contain activities that would be performed if additional resources were available. The timescale of human space exploration is envisioned to take many decades. The IRP illustrates the program s research plan through the timescale of early lunar missions of extended duration.

Source record↗

NASA NTRS2011

Low Cost Space Demonstration for a Single-Person Spacecraft

This paper introduces a concept for a single-person spacecraft and presents plans for flying a low-cost, robotic demonstration mission. Called FlexCraft, the vehicle integrates propulsion and robotics into a small spacecraft that enables rapid, shirt-sleeve access to space. It can be flown by astronauts or tele-operated and is equipped with interchangeable manipulators used for maintaining the International Space Station (ISS), exploring asteroids, and servicing telescopes or satellites. Most FlexCraft systems are verified using ground facilities; however, a test in the weightless environment is needed to assess propulsion and manipulator performance. For this, a simplified, unmanned, version of FlexCraft is flown on a low-cost launch vehicle to a 350 km circular orbit. After separation from the upper stage, the vehicle returns to a target box mounted on the stage testing the propulsion and control capability. The box is equipped with manipulator test items that are representative of tasks performed on ISS, asteroid missions, or for satellites servicing. Nominal and off-nominal operations are conducted over 3 days then the vehicle re-enters the atmosphere without becoming a debris hazard. From concept to management to operations, the FlexCraft demonstration is designed to be low cost project that is launched within three years. This is possible using a simplified test configuration that eliminates nine systems unique to the operational version and by designing-to-availability. For example, the propulsion system is the same as the Manned Maneuvering Unit because it capable, simple, human-rated and all components or equivalent parts are available. A description of the launch vehicle options, mission operations, configuration, and demonstrator subsystems is presented.

Griffin, Brand N.↗

NASA NTRS2017

Measuring the Effectiveness of Human Autonomy Teaming

Human-Automation Teaming (HAT), is now recognized as a promising solution to the problems of humans managing increasingly complex work systems. A human-automation team can be defined as the interdependent coupling between one or more human operators and one or more autonomous systems requiring collaboration and coordination to accomplish system and task goals (e.g., Langan-Fox et al., 2009). In this conception, automated agents are considered team members that can operate at various levels of automation, be focused on one or more human-information-processing stages, and the interactions with human operators may be adaptable, adjustable or mixed initiative. We investigated some metrics for assessing HAT effectiveness in a demonstration of a HAT tool used by ground station operators in a Reduced Crew Operations project that was conducted at NASA Ames Human Automation Teaming Laboratory. In this paper, we focus on operator metrics of HAT effectiveness, specifically workload and operator behaviors.

measurements↗

NASA NTRSDate not supplied

The History of EVA Safety at NASA

With NASA’s past and current involvement in Human Space Exploration in low Earth orbit and on the Moon, in lunar orbit and on the surface in the near future, and interplanetary space and the surface of Mars in the coming decades, the safety of the crew during Extravehicular Activity (EVA) remains paramount. EVAs during human space flight will challenge the crew and Mission Control for not only maintenance and reliability tasks but also exploration activities during a mission. Outside of launch and landing, EVA is the most dangerous crewed operation during a mission, making proper safety measures essential. This paper will explore how EVA safety operations havebeen managed throughout NASA’s history during the Gemini, Apollo, and Space Shuttle programs, how it is currently being managed for the International Space Station Program, and how these methods are planned to be utilized for Exploration efforts for human space flight into the future. Understanding the theory and processes that led to the documented safety requirements in the past and present will give insight into how to manage Exploration operations in the future, and may lead to process improvement with the advancements of technology in work today.

EVA↗

DOE OSTI2013

Failure Impact Analysis of Key Management in AMI Using Cybernomic Situational Assessment (CSA)

In earlier work, we presented a computational framework for quantifying the security of a system in terms of the average loss a stakeholder stands to sustain as a result of threats to the system. We named this system, the Cyberspace Security Econometrics System (CSES). In this paper, we refine the framework and apply it to cryptographic key management within the Advanced Metering Infrastructure (AMI) as an example. The stakeholders, requirements, components, and threats are determined. We then populate the matrices with justified values by addressing the AMI at a higher level, rather than trying to consider every piece of hardware and software involved. We accomplish this task by leveraging the recently established NISTR 7628 guideline for smart grid security. This allowed us to choose the stakeholders, requirements, components, and threats realistically. We reviewed the literature and selected an industry technical working group to select three representative threats from a collection of 29 threats. From this subset, we populate the stakes, dependency, and impact matrices, and the threat vector with realistic numbers. Each Stakeholder s Mean Failure Cost is then computed.

Algorithms↗

NASA NTRS2012

Developing an Open Source, Reusable Platform for Distributed Collaborative Information Management in the Early Detection Research Network

For the past decade, the NASA Jet Propulsion Laboratory, in collaboration with Dartmouth University has served as the center for informatics for the Early Detection Research Network (EDRN). The EDRN is a multi-institution research effort funded by the U.S. National Cancer Institute (NCI) and tasked with identifying and validating biomarkers for the early detection of cancer. As the distributed network has grown, increasingly formal processes have been developed for the acquisition, curation, storage, and dissemination of heterogeneous research information assets, and an informatics infrastructure has emerged. In this paper we discuss the evolution of EDRN informatics, its success as a mechanism for distributed information integration, and the potential sustainability and reuse benefits of emerging efforts to make the platform components themselves open source. We describe our experience transitioning a large closed-source software system to a community driven, open source project at the Apache Software Foundation, and point to lessons learned that will guide our present efforts to promote the reuse of the EDRN informatics infrastructure by a broader community.

Early Detection Research Network (EDRN)↗

NASA NTRS1974

Pioneer Odyssey: Encounter with a Giant

Ancient peoples, perhaps thousands of years ago, undoubtedly conceived the idea of "reaching out" to Jupiter, the largest and most brilliant of the "wandering stars." But for mankind to stretch across the half billion miles to the giant planet of the Solar System many advances in technical and organizational fields of human endeavor had to be made. Outreach to Jupiter did not become a serious possibility until the Pioneer F and G Project was formed by NASA early in 1968. And then man began to design an extension of his senses that would probe the environs of the giant of the Solar System, a truly pioneer odyssey into the virtually unknown regions beyond the orbit of Mars. In the ensuing year. a dedicated and cooperative effort of several thousand people in Government, university, and private industrial organizations converted the idea into a reality. Less than twelve generations after Galileo first saw the banded disc of Jupiter and the flickering dots of its large satellites in the newly invented telescope, mankind sent a machine to make observations within that Jovian system. The two Pioneer spacecraft for the mission to Jupiter each weighed only about 570 pounds, yet carried eleven highly sophisticated instruments capable of operating unattended for many year in space. The spacecraft consumes less electrical power than a standard 100 watt lamp yet is able to accept instructions from Earth to control numerous operating modes of its scientific payload, process observations from these scientific instruments and format the observations into information usable on Earth. Even more remarkable. the spacecraft transmits a radio signal of only 8 watts power - equal to a nightlight - yet the information carried by the radio signal is received back on Earth from a distance of several billion miles. The Pioneer mission could not have been a success without the special engineering, scientific and management organization created for its accomplishment. This organization was rather unique in that it first had to meet a launch date target relatively quickly and then had to function for an extremely long mission operational time, far longer than any previous mission to planets. The first task was thus to organize so that the mission could be planned and the spacecraft designed and fabricated to be ready for launch within a few weeks of a 30-month target for completion. The program also produced an organization that planned mission operations to such detail that more than 16,000 commands were transmitted flawlessly to the distant spacecraft during Jupiter encounter. And each command reached the spacecraft within one second of the planned time despite the more than 90 minutes required for the radio message to travel from Earth to the spacecraft and for the spacecraft to return a confirmation to controllers back on Earth. The organization for Pioneer also determined the required flight path from Earth to Jupiter with such precision, and controlled the launch vehicle with such accuracy, that 21 months after launch the spacecraft was able to fly behind Jupiter's satellite lo, thereby providing the first measurement that indicated the possibility of a tenuous atmosphere about this large satellite. Finally, the Pioneer organization processed and analyzed each year sufficient information from the spacecraft to fill a book having about 3 million pages and reduced this avalanche of data from space into summaries of manageable size. And all this organization depended on people, consisted of people: the people who really made this whole mission possible. Pioneer has always depended on the dedication of many individuals from many organizations throughout the world to achieve its scientific objectives, and, as evidenced by the success of the Pioneer series, this dependence is completely justified. Relatively few individuals have an opportunity during their lives to participate in such a challenging, historic, pioneering effort; and still fewer are able to enjoy the rewards of such an activity. We who have worked on Pioneer 10 and its sister spacecraft, Pioneer 11, consider ourselves fortunate to be in both classes. For the opportunity we thank the people of the United States of America, who have supported our country's space effort and its spreading of human awareness of a vast and intriguing universe in which our own unique planet Earth is only one of myriads of worlds. This volume describing the mission to Jupiter and its results is one of the many rewards for our effort which we share with you, the reader.

Fimmel, Richard O.↗