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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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

3D Gamma Source Mapping and Intervention Analysis - 19243

3D gamma source mapping and intervention analysis, through Transco Products, Inc.'s RadVision3D{sup R}, uses the N-Visage Scanner{sup TM} by Createc combining laser scanning, optical imaging, and CZT (Cadmium Zinc Telluride) technologies to capture plant geometry, images, and gamma radiation data. By capturing multiple scans in an area of interest a full 3D analysis can be performed using N-Visage Fusion{sup TM} software by Createc which develops a 3D model showing radioactive sources in the environment and allowing various interventions, such as shielding or source removal, to be modeled virtually. The output of a RadVision3D{sup R} project is a scaled virtual environment that the user can 'walk through' on a PC for training and work planning activities. Included in the viewer are dose planes for the as-scanned conditions as well as for each intervention, showing the dose rate at any point in the room. A virtual dosimeter is built into the viewer to allow users to be fully immersed in the environment in which they will be working, without being exposed to actual radiation or other hazardous conditions. This technology can help save dose at operating nuclear power plants when used for planning large work scopes in high radiation areas and is valuable as a characterization tool for decommissioning facilities. Adopters of 3D gamma source mapping and intervention analysis save time, money, and dose by evaluating options well in advance of the performance of any work, and optimizing interventions using accurate modelling techniques to plan work evolutions. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2011

Structures of segments of [alpha]-synuclein fused to maltose-binding protein suggest intermediate states during amyloid formation

Aggregates of the protein {alpha}-synuclein are the main component of Lewy bodies, the hallmark of Parkinson's disease. {alpha}-Synuclein aggregates are also found in many human neurodegenerative diseases known as synucleinopathies. In vivo, {alpha}-synuclein associates with membranes and adopts {alpha}-helical conformations. The details of how {alpha}-synuclein converts from the functional native state to amyloid aggregates remain unknown. In this study, we use maltose-binding protein (MBP) as a carrier to crystallize segments of {alpha}-synuclein. From crystal structures of fusions between MBP and four segments of {alpha}-synuclein, we have been able to trace a virtual model of the first 72 residues of {alpha}-synuclein. Instead of a mostly {alpha}-helical conformation observed in the lipid environment, our crystal structures show {alpha}-helices only at residues 1-13 and 20-34. The remaining segments are extended loops or coils. All of the predicted fiber-forming segments based on the 3D profile method are in extended conformations. We further show that the MBP fusion proteins with fiber-forming segments from {alpha}-synuclein can also form fiber-like nano-crystals or amyloid-like fibrils. Our structures suggest intermediate states during amyloid formation of {alpha}-synuclein.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

A Study on the Use of XCT and FEA to Predict the Elastic Behavior of Additively Manufactured Parts of Cylindrical Geometry

Defining general criteria for the acceptability of defects within industrial components is often complicated, since the specific load conditions and the criticality of the given application should be considered individually. In order to minimize the risk of failure, high safety factors are commonly adopted during quality control. However this practice is likely to cause the rejection of components whose defects would be instead acceptable if a more sound knowledge of the component behaviour were achieved. Parts produced by additive manufacturing (AM) may suffer from various defects, including micro- or macro-holes, delamination and microstructural discontinuities. Such processes, which are specially suitable for one-off components, require robust and reliable inspection before a part is accepted or rejected, since the refusal of even a single part at the end of the production process represents a significant loss. For this reason, it would be very useful to simulate in a reliable way whether a certain defect is truly detrimental to the proper working of the part during operation or whether the component can still be used, despite the presence of a defect. To this purpose, the paper highlights the benefits of a synergistic interaction between Industrial X-ray computed tomography (XCT) and finite element analysis (FEA). Internal defects of additively manufactured parts can be identified in a non-destructive way by means of XCT. Then FEA can be performed on the XCT-based virtual model of the real component, rather than on the ideal CAD geometry. A proof of concept of this approach is proposed here for a reference construct produced in an Aluminium alloy by AM. Numerical results of the proposed combined XCT–FEA procedure are contrasted with experimental data from tensile tests. The findings sustain the reliability of the method and allow to assess its full provisional accuracy for parts of cylindrical geometry designed to operate in the elastic field. The paper moves a step beyond the present application limits of tomography as it is currently employed for AM parts and it evidences instead the possibility of extending the usage of tomography to acceptance testing and prediction of operative behaviour.

42 ENGINEERING↗
DOE OSTI2020

Quantifying the effect of tow architecture variability on the performance of biaxially braided composite tubes

Targeted experiments are performed with stereoscopic digital image correlation to quantify the effect of irregular braid structure on the local surface mechanical response of carbon-fiber reinforced epoxy composite tubes. Virtual models comparing both nonuniform and uniform tow structure of the outer braid of each specimen are integrated into numerical simulations similar to experiments. Experimental and numerical results agree well. Statistical tests are used to support correlations between as-manufactured braid variation ranges to local increases in stress up to 18% compared to an ideal, uniform structure in the elastic regime. Results support improved manufacturing and modeling efforts of defect sensitive braided composites.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Software solutions manage the definition, operation, maintenance and configuration control of the National Ignition Facility

The National Ignition Facility (NIF) is the world's largest laser composed of millions of individual parts brought together to form one massive assembly. Maintaining control of the physical definition, status and configuration of this structure is a monumental undertaking yet critical to the validity of the shot experiment data and the safe operation of the facility. The NIF business application suite of software provides the means to effectively manage the definition, build, operation, maintenance and configuration control of all components of the National Ignition Facility. State of the art Computer Aided Design software applications are used to generate a virtual model and assemblies. Engineering bills of material are controlled through the Enterprise Configuration Management System. This data structure is passed to the Enterprise Resource Planning system to create a manufacturing bill of material. Specific parts are serialized then tracked along their entire lifecycle providing visibility to the location and status of optical, target and diagnostic components that are key to assessing pre-shot machine readiness. Nearly forty thousand items requiring preventive, reactive and calibration maintenance are tracked through the System Maintenance & Reliability Tracking application to ensure proper operation. Radiological tracking applications ensure proper stewardship of radiological and hazardous materials and help provide a safe working environment for NIF personnel.

42 ENGINEERING↗
DOE OSTI2026

Digital Twin Technology for Safety, Security, and Training in Spent Nuclear Fuel Handling

The increasing complexity of spent nuclear fuel handling requires significant resources to ensure safety, security, and personnel training. As nuclear facilities have continued to advance in scale and technology, the integration of digital tools has become indispensable. Among these tools, digital twins, which are virtual models of physical systems, are emerging as invaluable tools for enhancing safety protocols, security measures, and training in the nuclear sector. These models were conceptualized in the Industry 4.0 revolution. Digital twins can process data from physical systems in real time (by using sensors), include multiple code packages to enable simulations of different physics applications, and even implement artificial intelligence or machine learning techniques for advanced data processing. Despite the advantages that digital twins provide, challenges still exist regarding their widespread implementation. For instance, data used by a digital twin must be accurate to ensure that the digital twin is accurately tuned. Furthermore, if insecure digital twins are targeted by hackers, then they can pose serious risks to the security and safety of nuclear facilities.

Digital twins↗
DOE OSTI2025

High-throughput spin-bath characterization of spin defects in semiconductors

Detailed knowledge of the local environments of spin defects in semiconductors, such as nitrogenvacancy (NV) centers in diamond or divacancies in silicon carbide, is crucial for optimizing control and entanglement protocols in quantum sensing and information applications. However, at present a direct experimental characterization of individual defect environments is not scalable, as conventional spin-bath measurements are time consuming and difficult to automate. Achieving high-throughput characterization requires short experiments to probe the spin bath. However, with fewer and noisier measurements, the inverse problem of recovering spin-bath properties from measured data becomes ill posed, with multiple spin baths having a high likelihood of yielding the same data. In this work, we present a set of computational tools to resolve the ill-posed inverse problem of recovering the atomic positions and hyperfine couplings of random nuclei surrounding spin defects from sparse, noisy experimental coherence data, which can be obtained in hours. Here, we use a trans-dimensional Bayesian approach that incorporates ab initio data to yield full posterior distributions over nuclear spin environments, enabling robust recovery from limited data. We also provide practical tools and guidelines to determine the limits of detectability for hyperfine couplings under specific dynamical decoupling sequences and sampling conditions. In addition, we demonstrate how the tools developed here, in combination with ab initio simulations of spin baths, can guide the design of efficient experimental protocols for application-specific high-throughput screening. To showcase the utility of our approach, we apply it to design fast dynamical decoupling experiments to characterize the spin baths often individual NV centers in diamond. While the primary focus is on accelerating spin-bath characterization of spin defects, this Bayesian approach also lays the foundation for digital-twin studies of spin defects, where a virtual model of the spin-defect system evolves in real time with ongoing experimental measurements. Together, the set of tools we designed and applied paves the way for scalable deployment of spin defects in semiconductors for quantum sensing and information applications.

Bayesian methods↗
DOE OSTI2018

Forecasting and Early Warning for Adversarial Targeting in Industrial Control Systems

A new feature-based forecasting framework of abnormalities is presented for early warning for cyber-physical control systems. The abnormalities may refer to intelligent cyber-attacks or naturally occurring faults and failures. Techniques presented here are aimed at protecting against unauthorized intrusions as well as fault prevention. Time series signals from system monitoring nodes are converted to features using feature discovery techniques. The feature behavior for each monitoring node is characterized in the form of decision boundaries, separating normal and abnormal space with operating data collected from the plant or by running virtual models of the plant. A set of ensemble state-space models are constructed for representing feature evolution in time-domain, where the ensembles are selected using Gaussian Mixture Model (GMM) clustering. The forecasted outputs are anticipated time-evolution of features, computed by applying an adaptive Kalman predictor to each ensemble model. The overall features forecast is then obtained through dynamic ensemble averaging. This is done by projecting evolution of feature vector to future times in a receding horizon fashion. The features forecast are compared to the decision boundary to estimate if/when the feature vectors will cross the boundary. Simulation results in a high fidelity GE gas turbine platform, show the effectiveness of our approach for forecasting abnormalities.

42 ENGINEERING↗
DOE OSTI2016

TU-H-BRA-04: A Novel Superconducting Magnet Design for Optimized Patient Access and Minimal SSD for Use in a Linac-MR Hybrid

Purpose: A prototype rotating hybrid MR imaging system and linac has been developed to allow for simultaneous imaging and radiation delivery parallel to B{sub 0}. However, the design of a compact magnet capable of rotation in a small vault with sufficient patient access and a typical clinical source-to-surface distance (SSD) is challenging. This work presents a novel superconducting magnet design that allows for a reduced SSD and ample patient access by moving the superconducting coils to the side of the yoke. The yoke and pole-plate structures are shaped to direct the magnetic flux appropriately. Methods: The surface of the pole plate for the magnet assembly is optimized. The magnetic field calculations required in this work are performed with the 3D finite element method software package Opera-3D. Each tentative design strategy is virtually modeled in this software package and externally controlled by MATLAB, with its key geometries defined as variables. The particle swarm optimization algorithm is used to optimize the variables subject to the minimization of a cost function. At each iteration, Opera-3D will solve the magnetic field solution over a field-of-view suitable for MR imaging and the degree of field uniformity will be assessed to calculate the value of the cost function associated with that iteration. Results: An optimized magnet assembly that generates a homogenous 0.2T magnetic field over an ellipsoid with large axis of 30 cm and small axes of 20 cm is obtained. Conclusion: The distinct features of this model are the minimal distance between the yoke’s top and the isocentre and the improved patient access. On the other hand, having homogeneity over an ellipsoid give us a larger field-of-view, essential for geometric accuracy of the MRI system. The increase of B{sub 0} from 0.2T in the present model to 0.5T is the subject of future work. Funding Sources: Alberta Innovates - Health Solutions (AIHS)| Disclosure and Conflict of Interest: B. Gino Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta biplanar linac MR for commercialization).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

RANS Simulation VBM of Array of Three Coaxial Lab Scaled DOE RM1 MHK Turbine with 5D Spacing

Attached are the .cas and .dat files along with the required User Defined Functions (UDFs) and look-up table of lift and drag coefficients for the Reynolds Averaged Navier-Stokes (RANS) simulation of three coaxially located lab-scaled DOE RM1 turbine implemented in ANSYS FLUENT CFD-package. The lab-scaled DOE RM1 is a re-design geometry, based of the full scale DOE RM1 design, producing same power output as the full scale model, while operating at matched Tip Speed Ratio values at reachable laboratory Reynolds number (see attached paper). In this case study the flow field around and in the wake of the lab-scaled DOE RM1 turbines in a coaxial array is simulated using Blade Element Model (a.k.a Virtual Blade Model [VBM]) by solving RANS equations coupled with k-\omega turbulence closure model. It should be highlighted that in this simulation the actual geometry of the rotor blade is not modeled. The effect of turbine rotating blades are modeled using the Blade Element Theory. This simulation provides an accurate estimate for the performance of each device and structure of their turbulent far wake. The results of these simulations were validated against the developed in-house experimental data. Simulations for other turbine configurations are available upon request.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

Simulation of Blast and Behind-Armor Blunt Trauma to Life-Critical Organs in the Human Body [Poster]

Researchers at Sandia National Laboratories have developed a high-fidelity virtual model of the human head, neck, and torso to investigate the details of life-threatening injury to the central nervous, respiratory, and cardiovascular systems as a result of blast exposure and behind-armor blunt trauma. This model set is comprised of separate head-neck and torso models that can be used independently or combined to investigate comprehensive injury to life-critical organs as a result of blast, blunt impact, and/or projectile penetration. The Sandia head-neck-torso model represents a 60th percentile human male from the waist up possessing anatomically correct distributions of bone, white and gray brain matter, falx & tentorium membranes, spinal cord, intervertebral disks, cartilage, vasculature, blood, airways, lungs, heart, liver, stomach, kidneys, spleen, muscle, and fat/skin.

42 ENGINEERING↗
DOE OSTI2019

Final Report for Industrial Base Cybersecurity Initiative (IBCI) Project (FY2019)

Information security issues impact all manufacturing sectors and are particularly troublesome when designs for advanced weapons systems are lost via attacks that propagate through the relatively unprotected lower tiers of the nation's supply chains. The US Manufacturing Industrial Base (MIB) consists of suppliers and distributors that range in size from large prime contractors with extensive cybersecurity resources to small shops with little or no in-house information technology capabilities. The acquisition and maintenance of the technologies, systems, and financial resources needed to assure secure collaborations can be an overwhelming challenge for many manufacturers yet the cost of poor cybersecurity practices can lead to the compromise of national security information worth hundreds of millions of dollars. The Department of Defense Manufacturing Industrial Base Policy organization and the Department of Energy, Energy Efficiency and Renewable Energy Advanced Manufacturing Office have chartered the Los Alamos National Laboratory (LANL) and the Oak Ridge Y-12 National Security Complex (Y-12) to design, develop, and demonstrate a Manufacturing Threat Evaluation Wargaming System (MTEWS). The MTEWS concept is based on the use of a virtual model of the computer networks and cybersecurity protocols used across the MIB that will be continuously updated to reflect the dynamic threat environment. The MTEWS cyber-physical test range will demonstrate a prototype wargaming system that analyzes the impact of new and existing cybersecurity threats while also providing the information needed to sustain the integrity of the MIB supply chains. A long-term goal is the establishment of an enduring national manufacturing operations center that proactively responds to the continuously changing attacks that threaten the MIB and US national security. LANL and Y-12 have formed an Industrial Base Cybersecurity Initiative Team (IBCI), consisting of partners from the public, private and academic sectors, that is developing the MTEWS. To date, most of the project tasks have been centered on the technologies required to create a representative model of the MIB because this is a foundational element for the entire project. Modeling activities at the University of North Carolina at Charlotte (UNC Charlotte) have demonstrated a VMware-based prototype system that can accommodate a network model with up to 350 nodes and includes features such as the option to incorporate network scanning information when building the model and the ability to down select the elements of duplicative networks to a statistically significant subset that avoids redundantly duplicating network configurations. Broad Ordering Agreements have been established with UNC Charlotte and the University of West Florida (UWF) that support a variety of cybersecurity for manufacturing tasks and wide-spread endorsement has been received from government, industry and academia sectors concerning the IBCI goals and technical direction.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Cooperative Research and Development Agreement among National Energy Technology Laboratory, The Board of Regents of the University System of Georgia by and on behalf of Georgia Institute of Technology, and University of Texas at El Paso [Abstract]

Georgia Institute of Technology (GIT), University of Texas at El Paso (UTEP), and the National Energy Technology Laboratory (NETL) will collaborate and develop cyber-physical systems for advanced power systems. GIT will test virtual models on hybrid power system hardware and cyber physical components. UTEP will test novel actuators on hybrid power system hardware. NETL will access GIT’s expertise in the engineering and real time simulation of power system processes for cyber-physical systems and simulations to control hardware. NETL will establish a relationship to promote UTEP’s capabilities in additive manufacturing and high-temperature piezo-electric devices with the potential for controlling high-temperature flows with a light and inexpensive device at high response rates. This project is the result of an EERE Advanced Manufacturing Office open Multi-Topic awarded proposal led by GIT titled, “Robust Combined Heat and Hybrid Power (CHHP) for High Electrical Efficiency Cogeneration”.

42 ENGINEERING↗
DOE OSTI2024

An Autonomous Critical Data Extrapolator for the AGN-201m

Nuclear nonproliferation serves as a key goal, being undertaken by the International Atomic Energy Agency (IAEA). To recognize proliferation there are two pathways that states, who intend to use nuclear material for malicious purposes can take, diversion can misuse. Diversion is when fissile nuclear material is declared to the IAEA for non-weapon purposes, but then covertly removed. If the source of nuclear material, that is not declared and not fissionable, is placed inside the reactor core to create fissile material used to create weapons then the state is using the second pathway of proliferation, misuse. With the emerging development in areas of simulation and machine learning the creation of virtual models of reactor systems, digital twins, serve as a potential method to identify proliferation through detecting anomalous behavior in the reactor. A digital twin for a physical nuclear reactor has never been developed, as digital twins serve as an emerging technology. To investigate the process for development and use of a digital twin for a nuclear reactor Idaho State University’s AGN-201m serves as the nuclear reactor used for development of this digital twin. A data acquisition system has been installed to the reactor system allowing for the transfer of collected data from a reactor operation to Idaho National Laboratory’s Deeplynx data warehouse. When utilizing data to train reactor physics and machine learning models, a significant challenge encountered is the initial state of the data. Nuclear proliferation will have the capacity to be detected when the reactor immediately starts up, nor will it occur after the reactor shuts down. Generally, it will be detected when the reactor is operating at some desired power over a sufficient period for that specific reactor design. For the AGN-201m this will be when the reactor is critical (generally 1 mW or above) for a timespan that is within or less than the range of a regular business day. Datasets sent to Deeplynx have had to be manually cut to when the reactor is critical based on plots of power levels. This method is inefficient and laborious, especially when using multiple datasets at once to train a model. To provide a more streamlined approach an automated critical data extrapolator is developed, with capabilities of recognizing when the reactor operation first reaches criticality, and when the reactor undergoes a SCRAM and is shutdown.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Virtual Inspection of Advanced Manufacturing via Process-Scale Digital Twins (Abbreviated Report)

Inspection and certification comprise the most significant bottlenecks in advanced manufacturing for NNSA applications, often requiring far more time and resources than the fabrication of the parts themselves. Traditional methods, such as manual review and X-ray computed tomography, are not only slow and costly, but also struggle to provide a clear connection between manufacturing instructions and the final performance of critical components. This gap limits both the agility and assurance needed to support the modernization and safety of the United States nuclear stockpile. In response, our Strategic Initiative established a digital twin framework that integrates realtime process monitoring, automated data analysis, and immersive virtual reality collaboration into a unified inspection pipeline. By leveraging data from sensors, machine instructions, and imaging, we created high-fidelity virtual models of manufactured parts that could be rapidly analyzed and certified. This approach was first demonstrated with Direct Ink Write, and then extended to other manufacturing settings, including conventional (or “subtractive”) manufacturing and to predict the end of life performance of parts per the aging and lifetimes programs. The result is a transformational capability: inspection times have been reduced by a factor of 120,000 without loss of accuracy and while simultaneously improving traceability and confidence in part quality. This framework not only streamlines certification for critical applications, but also positions the national security enterprise to respond more flexibly to emerging challenges, supporting agile manufacturing and digital engineering practices across a broad range of mission-relevant domains.

42 ENGINEERING↗
DOE OSTI2024

Advanced manufacturing and digital twin technology for nuclear energy*

Advanced manufacturing techniques and digital twin technology are rapidly transforming the nuclear industry, offering the potential to enhance productivity, safety, and cost-effectiveness. Customized parts are being produced using additive manufacturing, automation, and robotics, while digital twin technology enables the virtual modeling and optimization of complex systems. These advanced technologies can significantly improve operational efficiency, predict system behavior, and optimize maintenance schedules in the nuclear energy sector, leading to heightened safety and reduced downtime. However, the nuclear industry demands the highest levels of safety and security, as well as intricate manufacturing processes and operations. Thus, challenges such as data management and cybersecurity must be addressed to fully realize the potential of advanced manufacturing techniques and digital twin technology in the nuclear industry. This comprehensive review highlights the critical role of digital twin technology with advanced manufacturing toward nuclear energy to improve performance, minimize downtime, and heighten safety, ultimately contributing to the global energy mix by providing dependable and low-carbon electricity.

36 MATERIALS SCIENCE↗
NASA NTRS1991

The Navy/NASA Engine Program (NNEP89): A user's manual

An engine simulation computer code called NNEP89 was written to perform 1-D steady state thermodynamic analysis of turbine engine cycles. By using a very flexible method of input, a set of standard components are connected at execution time to simulate almost any turbine engine configuration that the user could imagine. The code was used to simulate a wide range of engine cycles from turboshafts and turboprops to air turborockets and supersonic cruise variable cycle engines. Off design performance is calculated through the use of component performance maps. A chemical equilibrium model is incorporated to adequately predict chemical dissociation as well as model virtually any fuel. NNEP89 is written in standard FORTRAN77 with clear structured programming and extensive internal documentation. The standard FORTRAN77 programming allows it to be installed onto most mainframe computers and workstations without modification. The NNEP89 code was derived from the Navy/NASA Engine program (NNEP). NNEP89 provides many improvements and enhancements to the original NNEP code and incorporates features which make it easier to use for the novice user. This is a comprehensive user's guide for the NNEP89 code.

Plencner, Robert M.↗
NASA NTRS1999

Dan Goldin Presentation: Pathway to the Future

In the "Path to the Future" presentation held at NASA's Langley Center on March 31, 1999, NASA's Administrator Daniel S. Goldin outlined the future direction and strategies of NASA in relation to the general space exploration enterprise. NASA's Vision, Future System Characteristics, Evolutions of Engineering, and Revolutionary Changes are the four main topics of the presentation. In part one, the Administrator talks in detail about NASA's vision in relation to the NASA Strategic Activities that are Space Science, Earth Science, Human Exploration, and Aeronautics & Space Transportation. Topics discussed in this section include: space science for the 21st century, flying in mars atmosphere (mars plane), exploring new worlds, interplanetary internets, earth observation and measurements, distributed information-system-in-the-sky, science enabling understanding and application, space station, microgravity, science and exploration strategies, human mars mission, advance space transportation program, general aviation revitalization, and reusable launch vehicles. In part two, he briefly talks about the future system characteristics. He discusses major system characteristics like resiliencey, self-sufficiency, high distribution, ultra-efficiency, and autonomy and the necessity to overcome any distance, time, and extreme environment barriers. Part three of Mr. Goldin's talk deals with engineering evolution, mainly evolution in the Computer Aided Design (CAD)/Computer Aided Engineering (CAE) systems. These systems include computer aided drafting, computerized solid models, virtual product development (VPD) systems, networked VPD systems, and knowledge enriched networked VPD systems. In part four, the last part, the Administrator talks about the need for revolutionary changes in communication and networking areas of a system. According to the administrator, the four major areas that need cultural changes in the creativity process are human-centered computing, an infrastructure for distributed collaboration, rapid synthesis and simulation tools, and life-cycle integration and validation. Mr. Goldin concludes his presentation with the following maxim "Collaborate, Integrate, Innovate or Stagnate and Evaporate." He also answers some questions after the presentation.

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