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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Perspectives on future research directions in green manufacturing for discrete products

With the increasing concern due to climate change caused by a higher atmospheric concentration of CO 2 and other greenhouse gases, reducing environmental impact is becoming more important for every part of society. Manufacturing is responsible for a significant amount of energy/material consumption and environmental burden and, therefore, has a great opportunity to reduce its impact through green manufacturing. Green manufacturing presents opportunities across the manufacturing enterprise to increase the efficient usage of energy and material resources. These opportunities include designing products to consume fewer materials and energy during manufacturing and use, incorporating more efficient manufacturing processes, streamlining and optimizing manufacturing schedules and plans, and circularizing products. The goal of this paper will be to provide a perspective from the authors on the opportunities that exist within green manufacturing for discrete products through a review of pertinent topics and future directions. The paper will focus on processes, manufacturing equipment, manufacturing systems, recovering value at a product’s end-of-life, and additional thoughts that include metrics and indicators, techno-economic assessment, and a discussion of efficiency and effectiveness. Key findings from this review include a need for social indicators and renewable energy considerations in scheduling and process planning, integrating Industry 4.0 into circular economy along with social and institutional dimensions, consistency in the ability to measure and conceptualize metrics and indicators, a detailed evaluation of the life cycle impacts and cost of Addit Manuf, and more human and environment-oriented considerations for smart manufacturing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

LLMs for Mfg.—On the State of Large Language Models and Applications to Manufacturing

Additive Manufacturing (AM), referred to as 3D printing, has emerged as a key pillar of Industry 4.0 enabling layer-by-layer fabrication of intricate geometries from CAD models. In parallel, Large Language Models (LLMs), deep learning models for natural language generation trained on vast text corpora, have demonstrated unprecedented capabilities in understanding and generating human-like text. The convergence of these trends opens new opportunities at the intersection of AM and AI/ML, where LLMs can assist engineers and researchers in design, manufacture planning, and knowledge discovery. Recent academic work has begun to explore LLM applications in AM and adjacent fields, such as material science, mechanical engineering, and design for additive manufacturing. This exploration ranges from intelligent process planning to domain-specific knowledge retrieval. This survey provides a comprehensive review of current developments, focusing on peer-reviewed literature contributions that apply, adapt, and advance LLMs in general and domain-specific domains. We analyze state-of-the-art (SOTA) techniques, such as fine-tuning foundational models for specific domains, retrieval-augmented generation (RAG) pipelines, knowledge graph integration, and delve into the architectures and evaluation methods employed. The goal of this survey is to inform researchers and practitioners of the current capabilities and limitations of LLMs in general and in domain-specific applications, and to outline how these models are being tailored to meet the requirements of these applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Abrasive Waterjet Machining

The abrasive waterjet machining process was introduced in the 1980s as a new cutting tool; the process has the ability to cut almost any material. Currently, the AWJ process is used in many world-class factories, producing parts for use in daily life. A description of this process and its influencing parameters are first presented in this paper, along with process models for the AWJ tool itself and also for the jet–material interaction. The AWJ material removal process occurs through the high-velocity impact of abrasive particles, whose tips micromachine the material at the microscopic scale, with no thermal or mechanical adverse effects. The macro-characteristics of the cut surface, such as its taper, trailback, and waviness, are discussed, along with methods of improving the geometrical accuracy of the cut parts using these attributes. For example, dynamic angular compensation is used to correct for the taper and undercut in shape cutting. The surface finish is controlled by the cutting speed, hydraulic, and abrasive parameters using software and process models built into the controllers of CNC machines. In addition to shape cutting, edge trimming is presented, with a focus on the carbon fiber composites used in aircraft and automotive structures, where special AWJ tools and manipulators are used. Examples of the precision cutting of microelectronic and solar cell parts are discussed to describe the special techniques that are used, such as machine vision and vacuum-assist, which have been found to be essential to the integrity and accuracy of cut parts. The use of the AWJ machining process was extended to other applications, such as drilling, boring, milling, turning, and surface modification, which are presented in this paper as actual industrial applications. To demonstrate the versatility of the AWJ machining process, the data in this paper were selected to cover a wide range of materials, such as metal, glass, composites, and ceramics, and also a wide range of thicknesses, from 1 mm to 600 mm. The trends of Industry 4.0 and 5.0, AI, and IoT are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Chapter 6 - Polymer and composites additive manufacturing: material extrusion processes

This chapter focuses on material extrusion additive manufacturing (AM) processes for polymers and composite materials. Different extrusion AM platforms, along with their operating mechanism concepts, processing capabilities, and limitations, are discussed here. This chapter also covers state-of-the-art developments in new areas such as hybrid systems, integrated systems, and automation, which facilitate the integration of extrusion-based AM processes into smart manufacturing or Industry 4.0. Following this, a comprehensive discussion on materials development, criteria for successful printing of different materials (thermoplastics, thermosets, and their composites), key factors influencing printing, and material-related challenges in extrusion AM is presented. Finally, a brief overview of current and future potential applications of material extrusion AM technology is provided.

Kishore, Vidya↗
DOE OSTI2021

Developing a digital twin for hydropower systems - an open platform framework

The definition of digital twin in Wikipedia says “A digital twin is a virtual representation that serves as the real-time digital counterpart of a physical object or process.” Indeed, the digital twin (DT) concept was initially introduced at the start of the 21st century with intent to create a digital model to reflect physical systems and derive insight from the model to make the decision on system operation. DT is also a promising enabling technology for realising smart manufacturing and industry 4.0. In general, DTs consist of three main parts: physical product, virtual product, and connected data that link physical and virtual product via various data communication schemes.

13 HYDRO ENERGY↗
DOE OSTI2024

Detection of Control Injection Attacks using Energy Data Anomalies in CNC Machining

The widespread adoption of networked devices, sophisticated automation, and data-driven processes in the industry - also known as Industry 4.0 - has boosted the quantity and quality of manufacturing products. With these benefits, however, comes a substantial increase in the attack surface of these systems. In addition to affecting the readiness and the quality of critical products, the attacks against manufacturing processes and systems carry the potential to have severe physical consequences, including human injury and death. In this paper we present the results of a remote network-based control injection attack on a CNC mill. Specifically, we focus on the impact of this type of the attack on the movement of CNC mill during operation. Evaluating the physical effect of these attacks on a workpiece, we provide machine agnostic, affordable, and scalable solution for their monitoring. We then demonstrate a simple threshold-based method for the detection of these attacks and evaluate the effectiveness of detection.

Taylor, Curtis↗
DOE OSTI2023

CommAwareNet: Towards Communication‐Aware Smart Facilities: Designing an Energy‐Efficient High‐Data‐Rate and Reliable Hybrid THz/VLC Comm. Arch. Reinforced with Intelligent Surfaces for Future Network

This project will develop foundations for energy-efficient, high-data-rate, and reliable communication links for next-generation advanced wireless technologies. The Internet of Everything is emerging as a major technology that can establish a massively connected network among both human-type users and machine-type devices. Particularly, massive machine-type communication is becoming the dominant communication paradigm for numerous emerging areas, including data center networking and wireless backhaul, healthcare (e-health), manufacturing (industry 4.0), utilities, transportation (connected cars and public safety), and virtual or augmented reality for human-machine interaction applications. The rising demand for high data rates, especially in indoor scenarios and densely populated outdoor environments, will eventually overload conventional RF-based technologies. This project aims to conduct fundamental research to design, optimize, and validate a communication-aware, energy-efficient, and reliable network (CommAwareNet) architecture for future smart facilities and environments that require unprecedented high throughput needs for massive numbers of the machine- and human-type users. The scientific and technical merit of this work lies in the research required to bring the proposed transformative CommAwareNet solution into fully functional and practical architecture.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Towards developing multiscale-multiphysics models and their surrogates for digital twins of metal additive manufacturing

Artificial intelligence (AI) embedded within digital models of manufacturing processes can be used to improve process productivity and product quality significantly. The application of such advanced capabilities particularly to highly digitalized processes such as metal additive manufacturing (AM) is likely to make those processes commercially more attractive. AI capabilities will reside within Digital Twins (DTs) which are living virtual replicas of the physical processes. DTs will be empowered to operate autonomously in a diagnostic control capacity to supervise processes and can be interrogated by the practitioner to inform the optimal processing route for any given product. The utility of the information gained from the DTs would depend on the quality of the digital models and, more importantly, their faster-solving surrogates which dwell within DTs for consultation during rapid decision-making. In this article, we point out the exceptional value of DTs in AM and focus on the need to create high-fidelity multiscale-multiphysics models for AM processes to feed the AI capabilities. We identify technical hurdles for their development, including those arising from the multiscale and multiphysics characteristics of the models, the difficulties in linking models of the subprocesses across scales and physics, and the scarcity of experimental data. We discuss the need for creating surrogate models using machine learning approaches for real-time problem-solving. We further identify non-technical barriers, such as the need for standardization and difficulties in collaborating across different types of institutions. We offer potential solutions for all these challenges, after reflecting on and researching discussions held at an international symposium on the subject in 2019. Here, we argue that a collaborative approach can not only help accelerate their development compared with disparate efforts, but also enhance the quality of the models by allowing modular development and linkages that account for interactions between the various sub-processes in AM. A high-level roadmap is suggested for starting such a collaboration.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Smart Manufacturing Pathways for Industrial Decarbonization and Thermal Process Intensification

Rapid decarbonization is fast becoming the primary environmental and sustainability initiative for many economic sectors. Industry consumes more than 30 % of all primary energy in the United States and accounts for nearly 25 % of all greenhouse gas (GHG) emissions. More than 70 % of energy consumed by the industrial sector is related to thermal processes, which are also the largest contributors of carbon emissions, overwhelmingly due to the combustion of fossil fuels. Thermal process intensification (TPI) seeks to dramatically improve the energy performance of thermal systems through technology pillars focusing on alternative energy sources and processes, supplemental technologies, and waste heat management. The impacts of TPI have significant overlap with the goals of industrial decarbonization (ID) that seeks to phase out all GHG emissions from industrial activities. Emerging supplemental technologies such as smart manufacturing (SM) and the industrial internet of things (IoT) enable significant opportunities for the optimization of manufacturing processes. Combining strategies for TPI and ID with SM and IoT can open and enhance existing opportunities for saving time and energy via approaches such as tighter control of temperature zones, better adjustment of thermal systems for variations in production levels and feedstock properties, and increased process throughput. Data collected by smart processes will also enable new advanced solutions such as digital twins and machine learning algorithms to further improve thermal system savings. Herein, this paper examines the individual pathways of TPI, ID, and SM and how the combination of all three can accelerate energy and GHG reductions.

42 ENGINEERING↗
DOE OSTI2025

Electric Drive Technologies Consortium (EDTC)/ Cost competitive, high-Performance, highly Reliable (CPR) Power Devices on 4H-SiC (Final Report)

4H-Silicon carbide (4H-SiC) is a wide bandgap semiconductor that offers superior material properties over silicon, including higher critical electric field, thermal conductivity, and electron saturation velocity. These advantages make 4H-SiC highly attractive for high-voltage, high-efficiency power electronics. However, realizing the full potential of SiC requires device technologies that are not only high-performing but also manufacturable and reliable under real-world operating conditions. This report summarizes the outcomes of a five-year R&D effort funded by the U.S. Department of Energy (DOE) under the Electric Drive Technologies Consortium (EDTC), focused on developing cost-competitive, high-performance, and highly reliable (CPR) power devices on 4H-SiC substrates. The program targeted scalable and manufacturable 1.2 kV-class SiC MOSFETs optimized for next-generation electric vehicles, renewable energy systems, and industrial power conversion. The project delivered transformative advancements in SiC power device performance and ruggedness. Particularly, Specific on-resistance (R on,sp ) was reduced by up to 37%, from ~4.0 m$\Omega \cdot$cm 2 in earlier designs to an industry-leading 2.40 m$\Omega \cdot$cm 2 , driven by optimized doping, refined JFET widths, and layout engineering. Breakdown voltages (BV) exceeded 1600 V, marking improvement over legacy baselines, and demonstrating the robustness of newly implemented junction profiles and edge terminations. Short-circuit withstand time (SCWT) saw a remarkable 4$\times$ increase, from ~2 $\mu$s to over 8 $\mu$s, achieved through the successful deployment of deep P-well structures (~1.8–2.0 $\mu$m) via channeling implantation. This innovative process breakthrough enabled precise junction formation without MeV-class implantation tools, reduced leakage under high field stress, and allowed even the shortest-channel devices (down to 0.3 $\mu$m) to achieve both high BV and excellent ruggedness—breaking the traditional trade-off between conduction efficiency and blocking capability. Several novel architectures pushed the performance envelope further. JBSFETs—featuring embedded Schottky portions—eliminated bipolar degradation and drastically reduced third-quadrant leakage, while Ladder MOSFETs introduced a clever orthogonal conduction path that achieved a 15.4% reduction in R on,sp over standard linear designs. Switching performance reached new benchmarks: short-channel devices showed a 31% reduction in total switching energy compared to 0.5 $\mu$m counterparts, while maintaining manageable gate drive requirements. Layout-optimized structures not only improved transconductance but also accelerated switching transitions, pointing to real-world benefits in converter-level efficiency. The devices also passed rigorous reliability validation. Stress-tested across TDDB, HTGB, HTRB, HVP, and burn-in, the devices screened under 30 V/10 hr and 43 V/1 s protocols consistently exhibited tighter lifetime distributions and long-term oxide robustness. These screening techniques proved effective in identifying latent defects and ensuring deployment-grade reliability. Meanwhile, advanced 3D TCAD simulations revealed and resolved electric field hotspots—particularly in HEXFET corners—where fields exceeding 4.8 MV/cm were mitigated through geometry-aware layout corrections. Overall, the results of this project demonstrate a manufacturable and scalable SiC power device platform that addresses key DOE performance targets for efficient, robust, and reliable 1.2kV 4H-SiC Power Devices. The developed technologies represent a meaningful step forward in the commercial readiness of high-voltage SiC solutions and provide a strong foundation for continued advancement in wide bandgap power electronics.

42 ENGINEERING↗
DOE OSTI2021

A comprehensive and synthetic dataset for global, regional, and national greenhouse gas emissions by sector 1970–2018 with an extension to 2019

To track progress towards keeping global warming well below 2 °C or even 1.5 °C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO 2 emissions, CH 4 emissions, N 2 O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF 6 , NF 3 ) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO 2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (~ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO 2 eq. consisting of CO 2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO 2 , CO 2 -LULUCF 5.7 ± 4.0 GtCO 2 , CH 4 10 ± 3.1 GtCO 2 eq., N2O 2.6 ± 1.6 GtCO 2 eq., and F-gases 1.3 ± 0.40 GtCO 2 eq. Initial estimates suggest further growth of 1.3 GtCO 2 eq. in GHG emissions to reach 59 ± 6.6 GtCO 2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr –1 ) compared to 2000–2009 (2.4 % yr –1 ), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Metal Scrap Upcycling with Shear Assisted Processing and Extrusion (ShAPE)

The overarching objective of this project is to convert metal scraps, such as aluminum, titanium, and other alloys provided by the industry, into extruded tubing, wires, and rods. Upcycling of scrap will be accomplished using Shear Assisted Processing and Extrusion (ShAPE). This approach is a new solution for recycling. The specific aims of this project are as follows: 1. Receive metal scrap under a Material Transfer Agreement (MTA), in the form of billets, from select industry partners that meet the following requirements: outer diameter of 1.245 inches (+/-0.003 inches), inner diameter drilled with a 0.404-inch drill bit, and a length of 4.0 inches (+/-0.01 inches). The billet must be cast or compacted to greater than 98% density. If the industry partner does not have the capabilities to prepare the billets, PNNL can make introductions to third-party entities as needed. Industry partners will also provide a composition analysis as weight percent. 2. Extrude metal scrap via the ShAPE process at PNNL. 3. Evaluate and benchmark the extrudate material properties per the ASTM B557-15 – Testing Tubulars Standard or similar wire and rod standards. 4. Characterize the extrudate microstructure for any of the following: grain size, second phase composition, and texture. Additional testing may include corrosion per the ASTM B117 standard and electro-potential. 5. Deliver specimens to industry partners under an MTA for additional third-party evaluations. Industry partners will, in return, provide a non-proprietary report on any testing, including testing per the ASTM B557-15, ASTM B117, and other industry standards. 6. PNNL will develop data and insights to support intellectual property capture, a published non-proprietary technical report, research collaborations, and commercialization opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

OPERATOR 4.0 FOR HYBRID MANUFACTURING

Hybrid manufacturing, a combination of additive and subtractive manufacturing capabilities in one system, has recently become a more viable production option across several industries. Although current hybrid manufacturing research covers a broad range of topics, there is a lack of focus on how this new technology impacts both the designer and the operator of hybrid systems. This paper identifies areas of literature across design theory and Industry/Operator 4.0 research efforts and presents a path for applying this research to hybrid manufacturing users. The unique relationship between operator and designer is highlighted as they learn new strategies and develop new intuitive judgements over time to become the first experienced/expert users of hybrid manufacturing. The potential impact of excessive cognitive workload due to the novel combination of processes is discussed. This paper begins a critical discussion about proper knowledge transfer to other hybrid designers and operators, as well as towards efforts of monitoring, inspecting, and automating hybrid manufacturing processes.

Fillingim, Blane↗
DOE OSTI2023

Supplement to M&V Guidelines: Measurement and Verification for Performance-Based Contracts Version 4.0

Measurement and verification (M&V) are key to determining and confirming the continued operation of, and savings associated with, performance-based contracts. The Federal Energy Management Program (FEMP) updates these guidelines to reflect the evolution of M&V to incorporate industry best practices and ensure that savings from these performance-based projects are properly planned, communicated, and realized. FEMP released M&V Guidelines: Measurement and Verification for Federal Energy Projects Version 3.0 in 2008. This document was developed with input from industry-government working groups, previous M&V guideline authors, and national laboratory subject matter experts. The document provided the methods and guidelines, with a focus on federal energy savings performance contracts (ESPCs). When FEMP released M&V Guidelines: Measurement and Verification for Performance-Based Contracts Version 4.0 in 2015, FEMP expanded the intended audience to include anyone (energy managers, procurement officers, and contractors) involved in implementing performance-based contracts. The streamlined M&V Guidelines Version 4.0 provided the procedures and guidelines needed to quantify savings resulting from installing energy-efficient equipment, water conservation, improved operation and maintenance (O&M), renewable energy, and cogeneration projects with a performance-based contract; however, it removed some of the associated details on topics such as developing regression models and sampling plans. The details and information provided in M&V Guidelines v. 3.0 are still pertinent to M&V for performance-based contracts. The objective is to keep FEMP M&V version 4.0 condensed, providing the reference document for specifying M&V methods and procedures and a resource for developing project-specific M&V plans; this supplement provides additional details. The content of this supplement has been updated to include pertinent revisions between M&V version 3.0 and M&V version 4.0 by providing details and updating the content to ensure relevancy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2011

Source Lines Counter (SLiC) Version 4.0

Source Lines Counter (SLiC) is a software utility designed to measure software source code size using logical source statements and other common measures for 22 of the programming languages commonly used at NASA and the aerospace industry. Such metrics can be used in a wide variety of applications, from parametric cost estimation to software defect analysis. SLiC has a variety of unique features such as automatic code search, automatic file detection, hierarchical directory totals, and spreadsheet-compatible output. SLiC was written for extensibility; new programming language support can be added with minimal effort in a short amount of time. SLiC runs on a variety of platforms including UNIX, Windows, and Mac OSX. Its straightforward command-line interface allows for customization and incorporation into the software build process for tracking development metrics. T

Monson, Erik W.↗
NASA NTRS1987

The economic payoff for a state-of-the-art high-efficiency flat-plate crystalline silicon solar cell technology

In 1986 during the flat-plate solar array project, silicon solar cells 4.0 sq cm in area were fabricated at the Jet Propulsion Laboratory (JPL) with a conversion efficiency of 20.1 percent (AM1.5-global). Sixteen cells were processed with efficiencies measuring 19.5 percent (AM1.5 global) or better. These cells were produced using refined versions of conventional processing methods, aside from certain advanced techniques that bring about a significant reduction in a major mechanism (surface recombination) that limits cell efficiency. Wacker Siltronic p-type float-zone 0.18-ohm-cm wafers were used. Conversion efficiencies in this range have previously been reported by other researchers, but generally on much smaller (0.5 vs. 4.0 cm) devices which have undergone sophisticated and costly processing steps. An economic analysis is presented of the potential payoffs for this approach, using the Solar Array Manufacturing Industry Costing Standards (SAMICS) methodology. The process sequence used and the assumptions made for capturing the economies of scale are presented.

Bickler, Donald B.↗
NASA NTRS2008

Intelligent Propulsion System Foundation Technology: Summary of Research

The purpose of this cooperative agreement was to develop a foundation of intelligent propulsion technologies for NASA and industry that will have an impact on safety, noise, emissions, and cost. These intelligent engine technologies included sensors, electronics, communications, control logic, actuators, smart materials and structures, and system studies. Furthermore, this cooperative agreement helped prepare future graduates to develop the revolutionary intelligent propulsion technologies that will be needed to ensure pre-eminence of the U.S. aerospace industry. This Propulsion 21 - Phase 11 program consisted of four primary research areas and associated work elements at Ohio universities: 1.0 Turbine Engine Prognostics, 2.0 Active Controls for Emissions and Noise Reduction, 3.0 Active Structural Controls and Performance, and 4.0 System Studies and Integration. Phase l, which was conducted during the period August 1, 2003, through September 30, 2004, has been reported separately.

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