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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2015

From the Soil to the Seed. Metal Transport in Arabidopsis

Deficiencies of micronutrients such as Fe, Mn, and Zn commonly limit plant growth and crop yields. The long-term goals of our program are to understand how plants acquire metal micronutrients from the soil and distribute them while protecting themselves from the potential redox damage metals can cause to living tissues. Metals serve as important co-factors for photosynthesis and respiration, yet we still know very little about metal transport. Our approach combines experimental and computational tools from the physical sciences with biochemistry and molecular biology. Specifically, we combine mutant analysis with synchrotron X-ray fluorescence (SXRF) spectroscopy, a technique that allows us to image the elemental composition of living plant material in 3-D. By analyzing the phenotypes of lines carrying mutations in various metal transporters, we have identified the genes responsible for uptake of zinc from the soil as well as genes involved in loading the seeds with metal micronutrients. Several of these transporters affect the localization of metals in the seed without affecting the overall metal content. Understanding how seeds obtain and store nutrients is key to developing crops with higher agronomic and nutritional value.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Many Body Methods from Chemistry to Physics: Novel Computational Techniques for Materials-Specific Modelling: A Computational Materials Science and Chemistry Network

Understanding the behavior of interacting electrons in molecules and solids so that one can predict new superconductors, catalysts, light harvesters, energy and battery materials and optimize existing ones is the ``quantum many-body problem’’. This is one of the scientific grand challenges of the 21 st century. A complete solution to the problem has been proven to be exponentially hard, meaning that straightforward numerical approaches fail. New insights and new methods are needed to provide accurate yet feasible approximate solutions. This CMSCN project brought together chemists and physicists to combine insights from the two disciplines to develop innovative new approaches. Outcomes included the Density Matrix Embedding method, a new, computationally inexpensive and extremely accurate approach that may enable first principles treatment of superconducting and magnetic properties of strongly correlated materials, new techniques for existing methods including an Adaptively Truncated Hilbert Space approach that will vastly expand the capabilities of the dynamical mean field method, a self-energy embedding theory and a new memory-function based approach to the calculations of the behavior of driven systems. The methods developed under this project are now being applied to improve our understanding of superconductivity, to calculate novel topological properties of materials and to characterize and improve the properties of nanoscale devices.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Advanced Simulation and Computing FY20 Implementation Plan (Rev. 0)

The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable the National Nuclear Security Administration (NNSA) to support stockpile requirements. The ultimate goal of the Stewardship Program, and thus the Advanced Simulation and Computing (ASC) Program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Site Environmental Report for 2016

Lawrence Berkeley National Laboratory (LBNL, Berkeley Lab) is a multi-program scientific facility operated by the University of California (UC) for the U.S. Department of Energy (DOE). Berkeley Lab’s research is focused on the physical, biological, environmental, and computational sciences with the objective of delivering scientific knowledge and discoveries pertinent to DOE’s mission. This annual report describes environmental protection activities and potential impacts resulting from LBNL operations conducted in 2016. The format and content of this report satisfy the requirements of both DOE Order 231.1B Admin Chg 1, Environment, Safety, and Health Reporting, and the operating contract between UC and DOE (DOE Contract No. DE-AC02-05CH11231, also known as Contract 31). Activities are planned and conducted with full regard to protecting employees, the public, and the environment, as well as complying with all applicable environmental, safety, and health laws and regulations. Berkeley Lab implements an Environmental Management System (EMS) to oversee these compliance activities and improve overall environmental performance while maintaining operational capability and sustaining its overall mission. The effectiveness of the EMS and environmental programs is reviewed annually as part of the operating contract’s performance evaluation process. For fiscal year (FY) 2016, which began October 1, 2015, and ended September 30, 2016, the EMS was given a performance rating of A minus for its management of environmental activities (on a scale from A plus as the highest grade to F as the lowest). The measurement and rating system was developed jointly by Berkeley Lab, UC, and DOE. The FY 2016 rating was based on how Berkeley Lab met the objective in DOE’s FY 2017 Performance Evaluation and Measurement Plan (Appendix B in Contract 31, Section J) of providing an efficient and effective EMS. To support this rating, Berkeley Lab prepared a list of projects completed during the performance period that achieved reduced environmental impacts. The EMS was also graded through the federal Office of Management and Budget’s EMS Annual Report Data, in which elements of the International Organization for Standardization (ISO) 14001 standard are rated and the degree of integration between the EMS and Berkeley Lab’s sustainable practices is measured. Overall scores fall into one of three categories: green (highest), yellow (middle), or red (lowest). For FY 2016, Berkeley Lab received a score of green, as described in more detail in Chapter 2. An overview of environmental protection and restoration programs is provided (Chapter 3), including information about compliance activities, operating permits, and regulatory agency inspections that occurred during 2016. Six minor violations issued during these inspections are discussed, one of which was rescinded in 2017. This report also includes information on environmental monitoring performed in 2016 (Chapter 4). The results of these monitoring activities confirmed that groundwater cleanup actions continue to show improving conditions, and all emissions and discharges from LBNL operations were within environmental compliance release limits with the exception of some stormwater discharges. While most stormwater discharges measured throughout the LBNL site fall within acceptable levels established by the state's stormwater permit, iron and aluminum exceeded permitted levels. Berkeley Lab is aggressively implementing controls to reduce iron and aluminum discharge levels. The controls include construction of asphaltic berms to restrain and filter runoff to storm drains, and installation of filtration units in storm drain basins to absorb metal contaminants. The radiological dose assessments (Chapter 5) performed in 2016 concluded that the maximum dose to a hypothetical resident from Berkeley Lab’s airborne radionuclide releases was approximately 0.12% of the DOE and U.S. Environmental Protection Agency annual limit of 10 millirem per year (mrem/year); the dose from all radiation sources at Berkeley Lab was approximately 0.1% of the average natural background radiation dose of 310 mrem/yr in the United States, and about 0.4% of the DOE annual limit of 100 mrem/yr from all sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Site Environmental Report for 2017

Lawrence Berkeley National Laboratory (LBNL, Berkeley Lab) is a multi-program scientific facility operated by the University of California (UC) for the U.S. Department of Energy (DOE). Berkeley Lab’s research is focused on the physical, biological, environmental, and computational sciences with the objective of delivering scientific knowledge and discoveries pertinent to DOE’s mission. This annual report describes environmental protection activities and potential impacts resulting from LBNL operations conducted in 2017. The format and content of this report satisfy the requirements of both DOE Order 231.1B, Administrative Change 1 (Environment, Safety, and Health Reporting) and the operating contract between UC and DOE (DOE Contract No. DE-AC02-05CH11231, also known as Contract 31). Activities are planned and conducted with full regard to protecting employees, the public, and the environment, as well as complying with all applicable environmental, safety, and health laws and regulations. Berkeley Lab implements an Environmental Management System (EMS) to oversee these compliance activities and continually improve overall environmental performance while maintaining operational capability and sustaining its overall mission. The effectiveness of the EMS and environmental programs is reviewed annually as part of the performance evaluation process of Contract 31. For fiscal year (FY) 2017, which began October 1, 2016, and ended September 30, 2017, the EMS was given a performance rating of B plus for its management of environmental activities (on a scale from A plus as the highest grade to F as the lowest). The measurement and rating system was developed jointly by Berkeley Lab, UC, and DOE. The FY 2017 rating was based on how Berkeley Lab met the objective in DOE’s FY 2017 Performance Evaluation and Measurement Plan (Appendix B in Contract 31, Section J) of providing an efficient and effective EMS. Six significant accomplishments, which ranged from effective teaming on projects and with regulatory agencies to improved program assessment approaches, were factors in the rating. The EMS was also graded through the federal Office of Management and Budget’s annual EMS performance metrics, in which a reporting scorecard rates elements of the International Organization for Standardization (ISO) 14001 standard and the degree of integration between the EMS and Berkeley Lab’s sustainable practices. Overall scores fall into one of three categories: green (highest), yellow (middle), or red (lowest). For FY 2017, Berkeley Lab received a score of green, as described in more detail in Chapter 2. An overview of environmental protection and restoration programs is provided, including information about compliance activities, operating permits, and regulatory agency inspections that occurred during 2017. Thirteen minor violations issued during City of Berkeley inspections of above and underground storage tanks, treatment units, and hazardous waste storage areas are discussed in this chapter. This report also includes information on environmental monitoring performed in 2017. The results of these monitoring activities confirmed that groundwater cleanup actions continue to show improving conditions, and all emissions and discharges from LBNL operations were within environmental compliance release limits, with the exception of some stormwater discharges. Most stormwater discharges measured throughout the LBNL site fall within acceptable levels established by the state’s stormwater permit; however, iron and aluminum exceeded Numeric Action Levels. To reduce iron and aluminum discharge levels, Berkeley Lab is aggressively implementing controls such as construction of asphaltic berms and check dams to restrain and filter runoff to storm drains, and installation of filtration units in storm drain basins to collect sediment and absorb metal contaminants. The radiological dose assessments performed in 2017 concluded that the maximum potential dose to a hypothetical resident from Berkeley Lab’s airborne radionuclide releases was approximately 0.1% of the DOE and U.S. Environmental Protection Agency annual limit of 10 millirem per year (mrem/yr); the potential dose from all radiation sources at Berkeley Lab was approximately 0.06% of the average natural background radiation dose of 310 mrem/yr in the United States, and about 0.2% of the DOE annual limit of 100 mrem/yr from all sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Site Environmental Report for 2018

Lawrence Berkeley National Laboratory (LBNL, Berkeley Lab) is a multi-program scientific facility operated by the University of California (UC) for the U.S. Department of Energy (DOE). Berkeley Lab’s research is focused on the physical, biological, environmental, and computational sciences, with the objective of delivering scientific knowledge and discoveries pertinent to DOE’s mission. This annual report describes environmental protection activities and potential impacts resulting from LBNL operations conducted in 2018. The format and content of this report satisfy the requirements of both DOE Order 231.1B, Administrative Change 1 (Environment, Safety, and Health Reporting) and the operating contract between UC and DOE (DOE Contract No. DE-AC02-05CH11231, also known as Contract 31). LBNL activities are planned and conducted with full regard to protecting employees, the public, and the environment, as well as complying with all applicable environmental, safety, and health laws and regulations. As presented in Chapter 2, Berkeley Lab implements an Environmental Management System (EMS) to oversee environmental compliance activities and continually improve overall environmental performance while maintaining operational capability and sustaining its overall mission. The effectiveness of the EMS and environmental programs is reviewed annually as part of the performance evaluation process of Contract 31. For fiscal year (FY) 2018, which began October 1, 2017, and ended September 30, 2018, the EMS was given a performance rating of B plus for its management of environmental activities (on a scale from A plus as the highest grade, to F as the lowest). The measurement and rating system was developed jointly by Berkeley Lab, UC, and DOE. The FY 2018 rating was based on how Berkeley Lab met the objective in DOE’s FY 2018 Performance Evaluation and Measurement Plan (Appendix B in Contract 31, Section J) of providing an efficient and effective EMS. Six significant accomplishments, which ranged from effective teaming on projects and with regulatory agencies to improved program assessment approaches, were factors in the rating. The EMS was also graded through the federal Office of Management and Budget’s annual EMS performance metrics, in which a reporting scorecard rates elements of the International Organization for Standardization (ISO) 14001 standard and the degree of integration between the EMS and Berkeley Lab’s sustainable practices. Overall scores fall into one of three categories: green (highest), yellow (middle), or red (lowest). For FY 2018, Berkeley Lab received a score of green. A week-long formal conformity audit of the EMS was conducted at the end of July by a qualified external party, as is required every three years. The audit team found that Berkeley Lab’s EMS continues to conform to the ISO standard with no major nonconformance. An overview of environmental protection and restoration programs is provided in Chapter 3, including information about compliance activities, operating permits, and regulatory agency inspections and audits that occurred during 2018. Twenty-one minor violations and two Class II violations were issued during agency inspections of programs governing aboveground and underground storage tanks, hazardous waste treatment units, hazardous waste storage areas, hazardous materials management, and wastewater, stormwater, and air emission sources. This report also includes information on environmental monitoring performed in 2018 (Chapter 4). The results of these monitoring activities confirmed that groundwater cleanup actions have been effective in reducing concentrations of volatile organic compounds (VOCs) in the groundwater, although concentrations appear to be reaching asymptotic levels in some areas. Site groundwater plumes are stable or are attenuating, and VOCs are not migrating off site. All emissions and discharges from LBNL operations were within environmental compliance release limits except oxides of nitrogen and carbon monoxide from boilers (under 5 million BTUs) from Buildings 2, 66, and 88. The radiological dose assessments (Chapter 5) performed in 2018 concluded that the maximum potential dose to a hypothetical resident from Berkeley Lab’s airborne radionuclide releases was approximately 0.04% of the DOE and U.S. Environmental Protection Agency annual limit of 10 millirem per year (mrem/yr); the potential dose from all radiation sources at Berkeley Lab was approximately 0.15% of the average natural background radiation dose of 310 mrem/yr in the United States, and about 0.5% of the DOE annual limit of 100 mrem/yr from all sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

[Office of Basic Energy Sciences (BES)] Roundtable on Producing and Managing Large Scientific Data with Artificial Intelligence and Machine Learning

To identify specific Priority Research Opportunities (PROs) for artificial intelligence and machine learning (AI/ML) at the US Department of Energy’s scientific user facilities, the Office of Basic Energy Sciences (BES) convened a roundtable of facility experts encompassing the fields of physics, chemistry, materials synthesis science, computational science, detector and accelerator technology, theory, modeling, simulation, and atomic-scale characterization techniques. The roundtable met on October 22–23, 2019, to identify coordinated, long-term AI/ML research efforts that will drive major advances in neutron, photon, and nanoscale sciences. This report describes the four PROs identified at the roundtable: PRO 1 on how AI/ML can extract high-value information from the large datasets; PRO 2 on how AI/ML can use such information in real time to maximize the facilities’ scientific output; PRO 3 on using AI/ML virtual laboratories (i.e., computational models of experimental facilities) to aid the facilities and user community in design and control of machine parameters and the design and execution of experiments, including training AI/ML models for PROs 1 and 2; and PRO 4 on how a shared scientific data infrastructure can provide tools to assemble and analyze the totality of data coming from user facilities. A section of the end of the report provides a summary on computer science and mathematics that highlights where enhanced AI/ML capabilities could be particularly impactful for BES user facilities.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

2021 Site Environmental Report (SER) for the Ernest Orlando Lawrence Berkeley National Laboratory (LBNL)

Lawrence Berkeley National Laboratory (LBNL, Berkeley Lab) is a multiprogram scientific facility operated by the University of California (UC) for the U.S. Department of Energy (DOE). Berkeley Lab’s research is focused on the physical, biological, environmental, and computational sciences, with the objective of delivering scientific knowledge and discoveries pertinent to DOE’s mission. This annual report describes environmental protection activities and potential impacts resulting from operations conducted in calendar year 2021, unless otherwise indicated. The format and content of this report satisfy the requirements of both DOE Order 231.1B, Administrative Change 1 (Environment, Safety, and Health Reporting) (DOE, 2012) and the operating contract between UC and DOE (DOE Contract No. DE-AC02-05CH11231, also known as Contract 31).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Look At Topics and Topic Clusters for DOE Laboratories, 1996 - 2021 [Slides]

Beginning in 2018, Elsevier through its Scopus database introduced topics to further refine its classification of publications: Previous classification schemes used concepts such as subject areas, e.g., physics and astronomy, chemistry, computer science, etc.; Topics, in contrast, are much more granular. There are over 96,000 and their titles/contents are very specific, e.g., “Multilayers; Interfaces (materials); Individual layer." Elsevier topic clusters or Clarivate citation topics represent good approaches to examining an institution’s scientific productivity areas. These approaches have the granularity that is not present in the previous categorization approaches used by these databases. The Elsevier topic clusters for the DOE Laboratories do not appear to vary that much over the 1996 – 2021 period. In some cases (ANL, LBNL, LANL, ORNL, and PNNL), there were over 1000 topic clusters at these Laboratories, but a consistent set formed the core of the publication activity. Diversity is viewed as a desirable property of a research portfolio. Examining the balance component of the DOE laboratories, the spread is uneven or not diverse. This may be due to the missions of these laboratories. The balance of a single university was unequal too.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Understanding Technical and Psychosocial Barriers to Realizing FAIR Data Process

The present study investigates barriers and facilitators to the implementation of Findable, Accessible, Interoperable, and Reusable (FAIR) data processes within the Physical Sciences Division of the Computational Sciences Directorate (PCSD). Employing a dual-method approach consisting of surveys and focus group discussions, the study aims to illuminate the complex interplay between technical and psychosocial factors that influence FAIR data adoption.

42 ENGINEERING↗
DOE OSTI2024

Analog Computing for Science

Conventional digital computing faces fundamental physical limits: large scale computing systems already con sume tens of Megawatts of power, Dennard scaling has ended, and data movement costs dominate application performance. Next generation experimental facilities generate data at rates that overwhelm conventional pro cessing and demand real-time analysis at the source. Analog computing, which exploits the continuous dynamics of physical systems to perform computation, promises a transformative path toward orders-of-magnitude gains in energy efficiency and time-to-solution for scientific workloads.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies

The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.

Computer Science↗
DOE OSTI2024

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science↗
NASA NTRS1982

Space Research and Technology Program: Program and specific objectives, document approval

A detailed view of the Space Research and Technology program work breakdown structure is provided down to the specific objective level. Goals or objectives at each of these levels are set forth. The specific objective narratives are structured into several parts. First, a short paragraph statement of the specific objective is given. This is followed by a list of subobjectives. A list of targets is then provided for those areas of the specific objective that are amenable to a quantitative description of technical accomplishment and schedule. Fluid and thermal physics, materials and structures, computer science and electronics, space energy conversion, multidisciplinary research, controls and human factors, chemical propulsion, spacecraft systems, transportation systems, platform systems, and spacecraft systems technology comprise the principal research programs.

Source record↗
NASA NTRS1990

Communications among data and science centers

The ability to electronically access and query the contents of remote computer archives is of singular importance in space and earth sciences; the present evaluation of such on-line information networks' development status foresees swift expansion of their data capabilities and complexity, in view of the volumes of data that will continue to be generated by NASA missions. The U.S.'s National Space Science Data Center (NSSDC) manages NASA's largest science computer network, the Space Physics Analysis Network; a comprehensive account is given of the structure of NSSDC international access through BITNET, and of connections to the NSSDC available in the Americas via the International X.25 network.

Green, James L.↗
NASA NTRS1999

NASA Tech Briefs, November 1999

Topics covered include: Computer-Aided Design and Engineering; Electronic Components and Circuits; Electronic Systems; Materials; Computer Programs; Mechanics; Machinery/Automation; Physical Sciences; Mathematics and Information Sciences; Books and Reports.

Source record↗
NASA NTRS2019

Complex Dynamics of Air Traffic Flow

Air traffic in the United States has continued to grow at a steady pace since 1980, except for a dip immediately after the tragic events of September 11, 2001. There are different growth scenarios associated both with the magnitude and the composition of the future air traffic. The Terminal Area Forecast (TAF), prepared every year by the FAA, projects the growth of traffic in the United States. Both Boeing and Airbus publish market outlooks for air travel annually. Although predicting the future growth of traffic is difficult, there are two significant trends: heavily congested major airports continue to see an increase in traffic, and the emergence of regional jets and other smaller aircraft with fewer passengers operating directly between non-major airports. The interaction between air traffic demand and the ability of the system to provide the necessary airport and airspace resources can be modeled as a network. The size of the resulting network varies depending on the choice of its nodes. It would be useful to understand the properties of this network to guide future design and development. Many questions, such as the growth of delay with increasing traffic demand and impact of the en route weather on future air traffic, require a systematic understanding of the properties of the air traffic network. There has been a major advance in the understanding of the behavior of networks with a large number of components. Several theories have been advanced about the evolution of large biological and engineering networks by authors in diversified disciplines like physics, mathematics, biology and computer science. Several networks exhibit a scale-free property in the sense that the probabilistic distribution of their nodes as a function of connections decreases slower than an exponential. These networks are characterized by the fact that a small number of components have a disproportionate influence on the performance of the network. Scale-free networks are tolerant to random failure of components, but are vulnerable to selective attack on components. This paper examines two network representations for the baseline air traffic system. A network defined with the 40 major airports as nodes and with standard flight routes as links has a characteristic scale: all nodes have 60 or more links and no node has more than 460 links. Another network is defined with baseline aircraft routing structure exhibits an exponentially truncated scale-free behavior. Its degree ranges from 2 connections to 2900 connections, and 225 nodes have more than 250 connections. Furthermore, those high-degree nodes are homogeneously distributed in the airspace. A consequence of this scale-free behavior is that the random loss of a single node has little impact, but the loss of multiple high-degree nodes (such as occurs during major storms in busy airspace) can adversely impact the system. Two future scenarios of air traffic growth are used to predict the growth of air traffic in the United States. It is shown that a three-times growth in the overall traffic may result in a ten-times impact on the density of traffic in certain parts of the United States.

Scale-free Networks↗