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Systems and methods for ultra-high reliability (UHR) wireless communications systems and methods are disclosed. The disclosed UHR wireless communications systems and methods make the networked components on a communications infrastructure robust to interference caused by unintentional jamming, intermittent connectivity, weather, and physical barriers.
Systems and methods for ultra-high reliability (UHR) wireless communications systems and methods are disclosed. The disclosed UHR wireless communications systems and methods make the networked components on a communications infrastructure robust to interference caused by unintentional jamming, intermittent connectivity, weather, and physical barriers.
The overall objective of the Department of Energy investigation into off-gas technology for molten salt reactors (MSR)s is to develop a list of functional requirements for an effective and reliable system. In collaboration with other elements of the Advanced Reactor Campaign ( denoted in italics ), the off-gas work package will address the following questions: 1. What is the composition of the gas stream going to the off-gas system ( chemistry and source term work package )? 2. What is the function of each off-gas treatment component, and how do they work? How efficient are they at removing or delaying fission and activation products? 3. What are the maintenance requirements of the off-gas system? 4. Is the system able to effectively detect and respond to off-normal events ( off-gas, source term, and simulation work packages )? 5. What measurement capabilities are possible now? What are the gaps? The objective of the off-gas project in fiscal year 2019 was to address the second, fourth, and fifth questions above. Thus, project has proceeded along two fronts: one focused on scrubber development at Oak Ridge National Laboratory and the other focused on spectroscopic detection of simulant fission product iodine at Pacific Northwest National Laboratory. A molten hydroxide scrubber was proposed for removal of both acidic gases, entrained mists, and particulates from a sparged molten salt off-gas. Hydroxide solutions are well known for their scrubbing ability and have been used in the off-gas systems of salt processing facilities. For the current project, a NaOH–KOH eutectic is being evaluated as a gettering medium. A laboratory-scale prototype glass scrubber was designed and built for the removal of aerosol simulants. The glass allows visualization of the scrubber operation, which is important for designing the stainless-steel housing for the NaOH–KOH eutectic. In parallel, Pacific Northwest National Laboratory has been developing optical sensors for detecting fission products and aerosol or mist species that could be entrained in the off-gas flow of an MSR. Efforts include Raman spectroscopy to identify and quantify iodine species such as I2 and ICl and laser-induced breakdown spectroscopy and laser-induced fluorescence for mists. Next year, these optical methods will be added to the hydroxide scrubber instrumentation to determine its effectiveness against airborne vapors and mists of concern.
In this study, we evaluate how an iterative portfolio approach compares to a more traditional capacity credit method, using the U.S. Southeast as a case study region. Using open-source planning and resource adequacy tools, we compare results using a capacity credit approximation method with those from iterating behind the two. We also explore how the iterative approach performs under a range of sensitivities, including higher load growth, regional coordination, and alternative weather years. We find that traditional capacity credit approximation methods can function well in today's system, but may face challenges for systems with higher levels of solar and storage. As such, integrating planning and resource adequacy models can address some of these gaps, helping planners deliver more reliable systems.
An overview of failure-tolerant control is presented, focusing on the control of continuous-time dynamic systems (or plants) whose motions can be represented by integrals of nonlinear ordinary differential equations. Failure tolerance may be called upon to improve system reliability, maintainability, and survivability, and the issues attached to achieving these goals are examined. Robustness, which is required in some degree by all failure-tolerant systems, is discussed. The use of parallel redundancy is examined. Analytical redundancy, the principal functions of which are failure detection, failure identification, and control-system reconfiguration, is also considered. The use of expert systems and neural networks is discussed.
New development in high reliability strapdown navigation platform using two-degree-of-freedom sensors and redundancy concept is presented in this paper. The development is based on the assumption that each axis of the sensor can fail without affecting the remaining axis. The systems reliability is investigated, the optimum redundancy configurations are proposed, a technique of sensor performance management is developed for the proposed systems.
Digital network reliability with redundancy to mask logic modules failure for asymmetric failure modes
The CCCTF was designed and installed at ORNL in the 1990s for high-temperature gas-cooled reactor accident simulation. It is located within a modular hot cell housed in the IFEL facility. In 2008 and 2009, modifications were made to the CCCTF in preparation for AGR safety testing. A new airlock was designed and installed to better support periodic exchange of the fission product deposition cups while maintaining the fuel at safety test temperature, and modifications were made to add routines to the existing user interface software for computer-controlled automation of the He sweep gas flow and liquid nitrogen supply to the 85Kr cold traps. However, the furnace control hardware and software remained essentially unchanged. At the conclusion of the AGR-1 and AGR-2 PIE campaigns, continued use of the CCCTF was in question because of the gradual obsolescence of the hardware and software used to control the furnace and ancillary systems that make up the CCCTF. Therefore, an effort was undertaken to replace all the obsolete components with new hardware and update the software to increase system reliability and ensure this capability’s maintenance for future research and fuel qualification efforts. The modifications included creating a new National Instruments (NI) LabVIEW-based control system with a graphical user interface (GUI).
In this paper the notion of normalized nonspecificity is introduced. The nonspecifity measures the uncertainty of the estimated parameters that reflect impairment in a controlled system. Based on this notion, a quantity called a reconfiguration coverage is calculated. It represents the likelihood of success of a control reconfiguration action. This coverage links the overall system reliability to the achievable and required control, as well as diagnostic performance. The coverage, when calculated on-line, is used for managing the redundancy in the system.
Quantification of the costs and benefits of electricity efficiency programs have focused largely on the economic value of annual energy reductions. State public utility commissions PUCs and utilities are increasingly interested in assessing peak demand impacts of these programs. The U.S. Energy Information Administration defines peak demand as "The maximum load during a specified period of time." In practice, utilities and grid operators use a wide range of definitions for peak demand. With increasing need for a more flexible and resilient electricity system, and changing costs for generation, utilities and other efficiency program administrators must take into account all characteristics of efficiency programs — including peak demand reduction — to ensure a reliable system at the most affordable cost. In this study, Berkeley Lab explored a new metric, the program administrator (PA) cost of saving peak demand (PA CSPD). We collected data on costs, energy savings and peak demand savings for electricity efficiency programs for 36 investor-owned utilities and other PAs in nine states (Arizona, Arkansas, California, Colorado, Illinois, Massachusetts, Maryland, New York and Texas) for 2014 to 2017. While some utilities report demand reductions for their electricity efficiency programs, there has been little sustained effort in the United States to gather peak demand reduction data or benchmark the cost of achieving peak demand impacts. As a first of its kind analysis, we developed a framework for analyzing peak demand savings across utilities and states and begin to quantify the cost of saving peak demand.
Theory and techniques applicable to design, analysis, and fault diagnosis of reliable spacecraft data systems
The results of the NASA F-8 digital fly-by-wire flight test program are presented, along with the implications for active controls applications. The closed loop performance of the digital control system agreed well with the sampled-data system design predictions. The digital fly-by-wire mechanization also met pilot flying qualities requirements. The advantages of mechanizing the control laws in software became apparent during the flight program and were realized without sacrificing overall system reliability. This required strict software management. The F-8 flight test results are shown to be encouraging in light of the requirements that must be met by control systems for flight-critical active controls applications.
The research is concerned with developing a new approach to enhancing fault tolerance of flight control systems. The original motivation for fault-tolerant control comes from the need for safe operation of control elements (e.g. actuators) in the event of hardware failures in high reliability systems. One such example is modem space vehicle subjected to actuator/sensor impairments. A major task in flight control is to revise the control policy to balance impairment detectability and to achieve sufficient robustness. This involves careful selection of types and parameters of the controllers and the impairment detecting filters used. It also involves a decision, upon the identification of some failures, on whether and how a control reconfiguration should take place in order to maintain a certain system performance level. In this project new flight dynamic model under uncertain flight conditions is considered, in which the effects of both ramp and jump faults are reflected. Stabilization algorithms based on neural network and adaptive method are derived. The control algorithms are shown to be effective in dealing with uncertain dynamics due to external disturbances and unpredictable faults. The overall strategy is easy to set up and the computation involved is much less as compared with other strategies. Computer simulation software is developed. A serious of simulation studies have been conducted with varying flight conditions.
Electric power system reliability is a crucial factor in the application of both manned and unmanned spacecraft that could alter the success of space exploration missions. Understanding the behavior of these electric systems is essential to determine the safe operating conditions, and subsequently, prevent undesired conditions which may cause system-wide blackouts, leaving the spacecraft in a vulnerable position. This study will use bifurcation analysis to determine the behavior of DC spacecraft electric power systems and identify the major causes of voltage instability.
Hazard Analysis, Failure Modes and Effects Analysis (FMEA), the Limited-Life Items List (LLIL), and the Single Point Failure (SPF) List were applied by System Safety and Reliability engineers on NASA's Communications, Navigation, and Networking reConfigurable Testbed (CoNNeCT) Project. The integrated approach involving cross reviews of these reports by System Safety, Reliability, and Design engineers resulted in the mitigation of all identified hazards. The outcome was that the system met all the safety requirements it was required to meet.
Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.
Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.
Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.