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Modified NRZ (non-return-to-zero) code immunizes record and playback systems against dc drift and bit slippage. In order to maximize bit packing density improved code called J-NRZ gives 100 percent NRZ efficiently and solves DC drift problem by adding check bits in specified format when long string is encountered. Remainder of data stream is encoded in NRZ format.
The Connected Traveler framework seeks to boost the energy efficiency of personal travel and the overall transportation system by maximizing the accuracy of predicted traveler behavior in response to real-time feedback and incentives. It is anticipated that this approach will establish a feedback loop that 'learns' traveler preferences and customizes incentives to meet or exceed energy efficiency targets by empowering individual travelers with information needed to make energy-efficient choices and reducing the complexity required to validate transportation system energy savings. This handout provides an overview of NREL's Connected Traveler project, including graphics, milestones, and contact information.
Global demand for transportation fuels is projected to increase 40% by 2040, and biomass-derived fuels (biofuels) play a crucial role in substituting fossil fuels and mitigating greenhouse gas emissions. Currently, biofuels are mainly consumed as blendstocks combined with petroleum-based fuels, and effective conversion technologies can address the quality challenges for offering standalone biofuels. Thermochemical conversion process is one of the most promising pathways among existing technologies for biofuel production. However, the major barriers are unwanted characteristics (e.g., thermal instability) of intermediate products, such as bio-oil, and required upgrading treatments for producing compatible fuels. Here, this study highlights the merits and critical challenges of thermochemical conversion and physicochemical upgrading technologies for bio-blendstock production from lignocellulosic biomass. The novelty of this study lies in potential directions for future research through both critical and systematic literature reviews, and the proposed intensified process for lignocellulosic-based fuel blendstocks production. It is concluded that recovery and fractionation strategies (e.g., quenching and stripping) can maximize process yields and add values in the efficient conversion pathways. Effective quenching can stop secondary free radical reactions and improve liquid yields over gas and solid yields. Stripping process can improve process yield, catalyst lifespan, and thermal stability. It is further concluded that physicochemical treatments are not as effective as thermochemical treatments, but have advantages of mild operating conditions and potential for integrated solutions in conjunction with other treatments.
A promising route for sustainable 1-butanol (butanol) production is ABE (acetone, butanol, ethanol) fermentation. However, recovery of the products is challenging because of the low concentrations obtained in the aqueous solution, thus hampering large-scale production of biobutanol. Membrane and adsorbent-based technologies using hydrophobic zeolites are interesting alternatives to traditional separation techniques (e.g., distillation) for energy-efficient separation of butanol from aqueous mixtures. To maximize the butanol over water selectivity of the material, it is important to reduce the number of hydrophilic adsorption sites. This can, for instance, be achieved by reducing the density of lattice defect sites where polar silanol groups are found. The density of silanol defects can be reduced by preparing the zeolite at neutral pH instead of using traditional synthesis solutions with high pH. In this work, binary adsorption of butanol and water in two silicalite-1 films was studied using in situ attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy under equal experimental conditions. One of the films was prepared in fluoride medium, whereas the other one was prepared at high pH using traditional synthesis conditions. The amounts of water and butanol adsorbed from binary vapor mixtures of varying composition were determined at 35 and 50 °C, and the corresponding adsorption selectivities were also obtained. Both samples showed very high selectivities (100–23 000) toward butanol under the conditions studied. The sample having low density of defects, in general, showed ca. a factor 10 times higher butanol selectivity than the sample having a higher density of defects at the same experimental conditions. This difference was due to a much lower adsorption of water in the sample with low density of internal defects. Analysis of molecular simulation trajectories provides insights on the local selectivities in the zeolite channel network and at the film surface.
Combining computational and experimental methods is a powerful approach to understand the variables that govern catalyst performance and ultimately design improved materials. However, the effectiveness of this approach rests on the strength of the relationships between calculated parameters and experimental measurements. These relationships are complicated by the intricacy and dynamic behaviour of catalytic active sites, and by the non-trivial relationship between calculated reaction energetics and observed rates. In this Perspective, we highlight opportunities to enhance the connection between computation and experiment in electrocatalysis. These include measuring the intrinsic kinetic behaviour of catalysts, creating precise models for the active site and its environment, and forming clear relationships between calculated reaction energetics and observed rates. As experimental and computational methods continue to become more powerful, clear connections between the two will maximize their utility to guide the design of efficient and selective electrocatalysts.
Meeting the diverse needs of user verticals requires innovative cellular architectures that can offer additional degrees of freedom to provide on-demand services. The terrestrial user-centric radio access network (UC-RAN) stands out as an excellent choice for this purpose. However, a drawback of UC-RAN is its tendency to prioritize high-priority verticals, often resulting in a subpar quality of experience for low-priority verticals. This issue is particularly exacerbated in hotspot areas. Here, to address this problem, we introduce an aerial network integrated with terrestrial UC-RAN to provide coverage to users which are not served by the terrestrial network. Furthermore, we analyze the impact of key configuration and optimization parameters (COPs), such as location, transmit power, altitude, and beamwidth of aerial base stations (ABSs) on system key performance indicators (KPIs), such as coverage, latency satisfaction, average spectral efficiency, and energy efficiency. We formulate a robust multiobjective function to maximize these KPIs without biasing toward any specific KPI(s). Finally, we propose a deep reinforcement learning optimization framework based on the state-of-the-art soft actor-critic algorithm to control ABS COPs and optimize system KPIs. Experimental evaluations demonstrate that the proposed optimization framework can converge to near-optimal solutions derived from the pseudo brute force in a few thousand epochs.
Abstract Solar thermal energy is trapped in a glass-covered water chamber/basin to provide the heat for evaporation of brackish water in a novel desalination system. To harvest clean water, a chimney is integrated with the water basin, which draws air into the chamber to be humidified by the vapor and then being ventilated via buoyance force. Uniquely, thermal conductive metal sheet is recommended to make the chimney, which allows the vapor in the humid air condenses easily when flowing up. The condensate at the inner wall of the chimney flows down to be collected as clean water. Mathematical modeling and numerical computation have been carried out to delineate the coupling of the buoyance-force-driven flow with the heat and mass transfer of air and water in the solar collection chamber and the condensation of vapor in the heat-dissipating chimney. The objective of the simulation and optimization of the system is to find the best match of the dimensions of the water chamber with a chimney to maximize the production of clean water and energy efficiency. The model has been used to simulation several cases (of water from 40 °C to 50 °C) with available experimental data from the authors’ previous work, and the agreement was satisfactory. The optimization studies found that there is a maximum air flowrate corresponding to a critical chimney height due to the requirement that the chimney is designated to dissipate heat as much as possible to condense water vapor. With the chimney height greater than the critical height, the airflow rate will have a slight decrease. Nevertheless, higher than a critical height is still needed for a chimney to condense more moisture. Optimized chamber diameters at different chimney heights are provided for reference of optimal system designs.
The leakage of solid-liquid phase change materials (PCMs) tremendously limits their long-term application in thermal energy storage (TES). In this work, we present durable and form-stable shape-stabilized PCMs (ss-PCMs) for TES in building envelopes. These ss-PCMs are fabricated by encapsulating polyethylene glycol (PEG) consisting of different molecular weights within mesoporous magnesium oxide and silica dioxide. For the first time, the phase transition temperature (Tt) of ss-PCMs has been fine-tuned synthetically to be comfortable to building occupants by utilizing PEG blends with molecular weights of 600 and 800 g/mol. Several parameters, including surface hydrophilicity/hydrophobicity, surface area, and PCM loading percentage, have been studied to maximize the latent heat enthalpy for high energy efficiency and maintain form stability. The best ss-PCM candidate with suitable Tt and appreciable latent heat enthalpy exhibits a repeatable phase change behavior for up to 1,000 thermal cycles without leakage, which provides a promising solution for durable TES in buildings. The Tt tunability extends its application over a wider temperature range beyond buildings.
The synthesis of thin silver films by the gas-jet deposition method is experimentally and theoretically studied. When the metal is deposited onto silicon substrates from a supersonic jet of silver vapor with a helium carrier gas, nanostructured films with a 3−30 nm size of nanostructures are obtained for a 1230−1380 K range of jet source temperatures. The data on Ag–He gas-jet dynamics when it is expanded into vacuum (velocity, temperature, concentration, flux of particles onto a substrate) depending on parameters at the source (vapor temperature, flow rate of a carrier gas) are obtained by the method of direct simulation Monte Carlo. The range of optimal helium flow rates, when the efficiency of a gas-jet source is maximal, is determined. It is established that the presence of a background gas in a deposition chamber at pressure higher than 1 Pa decreases the flow of particles onto a substrate, and a simple way of its evaluation is proposed. Conditions for formation of silver clusters in the jet are determined by using the simulation. It is shown that for experimental deposition regimes there are no clusters in the jet, and the observed silver nanostructures are formed on the substrate surface.
BOOTS is a package for optimal selection of candidate operating points in large-scale manufacturing applications. It is designed to optimally select operating points to maximize predicted values of product quality and resource efficiency according to a data-driven model. The package is based on the use of a multi-input multi-output (MIMO) Gaussian process model to describe the relationships between inputs (operating points) and outputs (product quality and resource efficiency). This package does not provide any site- or process-specific information.
Vast expanses of the ocean are characterized by extraordinarily low concentrations of nutrients but nevertheless support vibrant communities of marine microbes. In aggregate, these communities drive many of the important elemental cycles that sustain life on Earth. Microbial communities are organized to maximize nutrient and energy transfer between cells, and efficiently recycle organic carbon, nitrogen, phosphorus and trace metals. Energy and nutrient transfer occurs across a broad range of spatial scales. Large-sized marine algae and bacteria support epibiont communities that are physically in contact, exchanging nutrients and energy across cell membranes, while other communities that are physically far apart, rely on the horizontal mixing of ocean currents or the vertical pull of gravity to transfer nutrient and energy containing organic matter. Marine organic geochemists are making rapid progress in understanding the chemistry of the marine microbiome. These advances have benefited from parallel developments in analytical chemistry, microbial isolation and culture techniques, and advances in microbial genomics, transcriptomics, and proteomics. The combination of all three approaches has proven to be quite powerful. Here we highlight two aspects of the chemistry of organic phosphorus and trace metal cycling and the marine microbiome. In each study, advances in chemical analyses, microbial culture, and microbial genomics played key roles in understanding how microbial communities interact to facilitate nutrient cycling in the open ocean.
High energy particle physics and cosmology concern themselves with estimating fundamental parameters of nature, such as the masses and interactions of fundamental particles like the Higgs boson and the rate of expansion of the universe. In doing so, they analyze exabyte-scale datasets, some of the largest in all of science, and face many challenges in subsequent data analysis. These challenges are shared between the two disciplines, but we focus on particle physics to highlight one specific domain. In particle physics, the standard method for estimating parameters involves performing Monte Carlo (MC) integration as a function of both parameters of interest and nuisance parameters using an expensive simulator, counting the number of observed collision events (i.i.d. samples) from an experiment in the corresponding integration domains, and forming a Poisson likelihood function. This likelihood function is then used in a Frequentist manner to construct a maximum likelihood point estimate (MLE) and confidence set for the parameters. To sufficiently populate the high-dimensional integration domains, simulators consume billions of CPU-hours annually and produce hundreds of petabytes of intermediate output data. Several techniques have been developed to: optimize definitions of the integration domains so as to be maximally sensitive to a particular subset of parameters, efficiently estimate the integrals, and build robust surrogate models by interpolating between integral evaluations at different parameter points. One can view this whole endeavor as classical Simulation-Based Inference (SBI).
Introduction: Populus and its hybrids are attractive bioenergy crops and the southeastern United States has broad ability to supply bioenergy markets with woody biomass. Breeding and hybridization have led to superior eastern cottonwood (Populus deltoides W. Bartram ex Marshall) and hybrid poplars adapted to a wide variety of site types not suited for agricultural production. In order to maximize productivity and minimize inputs, genotypes need to efficiently use available site resources and tolerate environmental stresses. In addition, we need to determine plasticity of traits and their coordination across sites to select traits that will broadly characterize genotypes. Therefore, our study objectives were to determine (1) which leaf traits were correlated with growth, (2) if traits and genotypes exhibited significant plasticity across sites, and (3) how traits were coordinated within and across sites and Populus taxa. Methods: We measured trees at two sites in northeastern Mississippi, United States: one upland and one alluvial terrace site. Genotypes included eastern cottonwoods as well as F 1 crosses of eastern cottonwood and P. maximowiczii (Henry), P. nigra (L.) and P. trichocarpa (Torr. & Gray). Results: We found that sites differed in which leaf traits were correlated with productivity; with water use efficiency specifically being positively correlated with growth at an alluvial terrace site, but negatively correlated with growth at an upland site. Tree height growth, leaf isotope composition (δ 13 C and δ 15 N), as well as leaf mass per area (LMA) exhibited the least plasticity across sites, while physiological gas exchange parameters and leaf nitrogen concentration exhibited the highest plasticity. Broadly across taxa, leaf carbon isotope ratios were correlated with intrinsic water use efficiency, and stomatal conductance was positively correlated with photosynthetic nitrogen use efficiency across sites, while leaf nitrogen isotope ratios exhibited contrasting relationships with leaf nitrogen concentration. Discussion: Overall, these results allow us to refine selections of productive genotypes based on site conditions and site-specific relationships with physiological parameters to better match Populus taxa with sites and landowner objectives.
Buildings are becoming more data-rich. Building analytics tools, including energy information systems (EIS) and fault detection and diagnostic (FDD) tools, have emerged to enable building operators to translate large amounts of time-series data into actionable findings to achieve energy and non-energy benefits. To expedite data analytics adoption and facilitate technology innovation, building owners, technology developers, and researchers need reliable cost–benefit data and evidence-based guidance on deployment practices. This paper fulfills these needs with the energy use and survey data from a wide-ranging research and industry partnership program that covers thousands of buildings installed with analytics tools. The paper indicates that after two years of implementation, organizations using FDD tools and EIS tools achieved 9% and 3% median annual energy savings, respectively. The median base cost and annual recurring cost for FDD are USD 0.65 per square meter (m2) (USD 0.06 per square foot [ft2]) and USD 0.22 per m2 (USD 0.02 per ft2), and are USD 0.11 per m2 (USD 0.01 per ft2) and USD 0.11 per m2 (USD 0.01 per ft2) for EIS. The common metrics and analyses that are used in the tools to support the discovery of energy efficiency measures are summarized in detail. Two best practice examples identified to maximize the benefits of tool implementation are also presented. Opportunities to advance the state of technology include simplified data integration and management, and more efficient processes for acting on analytics outputs. Compared with previous efforts in the literature, the findings presented in this paper demonstrate the effectiveness of building analytics tools with the largest known dataset.
In order that the LST meet its scientific objectives and also be a National Astronomical Space Facility during the 1980's and 1990's, broad requirements have been levied by the scientific community. These scientific requirements can be directly translated into design requirements and specifications for the scientific instruments. The instrument ensemble design must be consistent with a 15-year operational lifetime. Downtime for major repair/refurbishment or instrument updating must be minimized. The overall efficiency and performance of the instruments should be maximized. Modularization of instruments and instrument subsystems, some degree of on-orbit servicing (both repair and replacement), on-axis location, minimizing the number of reflections within instruments, minimizing polarization effects, and simultaneous operation of the F/24 camera with other instruments, are just a few of the design guidelines and specifications which can and will be met in order that these broader scientific requirements be satisfied.-
This article deals with an auction mechanism for airspace slots, as a means of solving the European airspace congestion problem. A disequilibrium, between Air Traffic Control (ATC) services supply and ATC services demand are at the origin of almost one fourth of delays in the air transport industry in Europe. In order to tackle this congestion problem, we suggest modifying both pricing and allocation of ATC services, by setting up an auction mechanism. Objects of the auction will be the right for airlines to cross a part of the airspace, and then to benefit from ATC services over a period corresponding to the necessary time for the crossing. Allocation and payment rules have to be defined according to the objectives of this auction. The auctioneer is the public authority in charge of ATC services, whose aim is to obtain an efficient allocation. Therefore, the social value will be maximized. Another objective is to internalize congestion costs. To that end, we apply the principle of Clarke-Groves mechanism auction: each winner has to pay the externalities imposed on other bidders. The complex context of ATC leads to a specific design for this auction.
Gravity effects the growth and development of all living organisms. One of the most obvious manifestations of gravity's effects on biological systems lies in the ability of plants to direct their growth along a path that is dictated by the gravity vector (called gravitropism). When positioned horizontally, in florescence stems and hypocotyls in dicots, and pulvini in monocots, respond by bending upward whereas roots typically bend downward. Gravitropism allows plants to readjust their growth to maximize light absorption for photosynthesis and to more efficiently acquire water and nutrients form the soil. Despite its significance for plant survival, there are still major gaps in understanding the cellular and molecular processes by which plants respond to gravity. The major aim of this proposal was to develop improved fluorescence labeling techniques to aid in understanding how the cytoskeleton modulated plant responses to gravity.
Topics covered include: Active and Passive Hybrid Sensor; Quick-Response Thermal Actuator for Use as a Heat Switch; System for Hydrogen Sensing; Method for Detecting Perlite Compaction in Large Cryogenic Tanks; Using Thin-Film Thermometers as Heaters in Thermal Control Applications; Directional Spherical Cherenkov Detector; AlGaN Ultraviolet Detectors for Dual-Band UV Detection; K-Band Traveling-Wave Tube Amplifier; Simplified Load-Following Control for a Fuel Cell System; Modified Phase-meter for a Heterodyne Laser Interferometer; Loosely Coupled GPS-Aided Inertial Navigation System for Range Safety; Sideband-Separating, Millimeter-Wave Heterodyne Receiver; Coaxial Propellant Injectors With Faceplate Annulus Control; Adaptable Diffraction Gratings With Wavefront Transformation; Optimizing a Laser Process for Making Carbon Nanotubes; Thermogravimetric Analysis of Single-Wall Carbon Nanotubes; Robotic Arm Comprising Two Bending Segments; Magnetostrictive Brake; Low-Friction, Low-Profile, High-Moment Two-Axis Joint; Foil Gas Thrust Bearings for High-Speed Turbomachinery; Miniature Multi-Axis Mechanism for Hand Controllers; Digitally Enhanced Heterodyne Interferometry; Focusing Light Beams To Improve Atomic-Vapor Optical Buffers; Landmark Detection in Orbital Images Using Salience Histograms; Efficient Bit-to-Symbol Likelihood Mappings; Capacity Maximizing Constellations; Natural-Language Parser for PBEM; Policy Process Editor for P(sup 3)BM Software; A Quality System Database; Trajectory Optimization: OTIS 4; and Computer Software Configuration Item-Specific Flight Software Image Transfer Script Generator.