Engineering Papers⌕ Search

Engineering topics

Smith, Aaron

Publications and source records attributed to Smith, Aaron.

At least 19 records

Effective bias expansion for 21-cm cosmology in redshift space

A near-future detection of the 21-cm signal from the epoch of reionization will provide unique opportunities to probe the underlying cosmology, provided that such cosmological information can be extracted with precision. To this end, we further develop effective field theory (EFT) inspired techniques for the 21-cm brightness temperature field during the epoch of reionization, incorporating renormalized bias and a treatment of redshift space distortions. Notably, we confirm that in redshift space, measures of the 21-cm brightness, e.g., the power spectrum, should have irreducible contributions that lack a bias coefficient and therefore contain direct, astrophysics-free information about the cosmological density field; in this work, we study this effect beyond linear order. To validate our theoretical treatment, we fit the predicted EFT Fourier-space shapes to the thesan suite of hydrodynamical simulations of reionization at the field level, where the considerable number of modes prevents overfitting. We find agreement at the level of a few percent between the 21-cm power spectrum from the EFT fits and simulations over the wave number range k ≲ 0.8 h/Mpc and neutral fraction x HI ≳ 0.4, which is imminently measurable by the Hydrogen Epoch of Reionization Array and future experiments. Furthermore, the ability of the EFT to describe the 21-cm signal extends to simulations that have different astrophysical prescriptions for reionization as well as simulations with interacting dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗

Strategies for achieving circular economy goals in the lighting industry through design for disassembly- based methodologies

The significance of circular economy and its integration into core strategies for smart, sustainable, and inclusive growth, is increasingly being recognized by individuals, organisations, and nations in recent times. The term Design for Disassembly (DfD) may conjure up images about the end-of-life of a product or its disposal. However, DfD connects to numerous circularity and sustainability goals over the lifetime of a product or project and can have a large impact on the carbon footprint of the product. The DfD is a product development methodology which is in line with the vision of a circular economy, and supports increase in material efficiency, extends product lifetimes and improves recycling efficiency. Reduction of the imposed environmental risks and impact on the climate, by utilising circularity approaches such as remanufacturing, are tied to lowering of carbon footprint. This paper describes specific and actionable approaches that can be applied by luminaire manufacturers, specifiers, and other players in the lighting industry. The readers will learn about current tools and methodologies that can be used to improve iterative design, as well as measure, assess, and compare products or materials.

design for disassembly, dfd, circularity↗

2020 Solar Decathlon Education Partner: Cooperative Research and Development (Final Report, CRADA Number CRD-19-00802)

The U.S. Department of Energy Solar Decathlon (DOE/SD) is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. The DOE/SD is comprised of two Challenges--Design Challenge (annual, in April of each year at NREL in Golden, Colo.) and Build Challenge (biennial, held next in June/July 2020 in Washington D.C.). NREL provides competition management for DOE/SD. For over 35 years, EEBA has provided the most trusted resources for building science information and education in the construction industry. EEBA delivers turn-key educational resources and events designed to transform residential construction practices through high performance design, marketing, materials, and technologies. NREL and EEBA establish this CRADA to enable the success of the DOE/SD program in managing sponsorship funds and creating a professional education program. EEBA acted as an Education Partner to DOE/SD, which included: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing professional development content.

14 SOLAR ENERGY↗

Environmental outcomes of the US Renewable Fuel Standard

Biofuels are included in many proposed strategies to reduce anthropogenic greenhouse gas emissions and limit the magnitude of global warming. The US Renewable Fuel Standard is the world’s largest existing biofuel program, yet despite its prominence, there has been limited empirical assessment of the program’s environmental outcomes. Even without considering likely international land use effects, we find that the production of corn-based ethanol in the United States has failed to meet the policy’s own greenhouse gas emissions targets and negatively affected water quality, the area of land used for conservation, and other ecosystem processes. Our findings suggest that profound advances in technology and policy are still needed to achieve the intended environmental benefits of biofuel production and use.

54 ENVIRONMENTAL SCIENCES↗

NRWAL (NLR formerly known as NREL Wind Analysis Library) [SWR-21-26]

NRWAL (NLR (National Laboratory of the Rockies) formerly known as NREL (National Renewable Energy Laboratory) Wind Analysis Library: A library of offshore wind cost equations (plus new energy technologies like marine hydro!) Easy equation manipulation without editing source code Full continental-scale integration with the NREL Renewable Energy Potential Model (reV) https://nrel.github.io/reV/ Ready-to-use configs for basic users Dynamic python tools for intuitive equation handling One seriously badass sea unicorn To get started with NRWAL, check out the NRWAL Config documentation or the NRWAL example notebook. You can also launch the notebook in an interactive jupyter shell right in your browser without any downloads or software using binder. Ready to build a model with NRWAL but don't want to contribute to the library? No problem! Check out the example getting started project here. Here is the important stuff: The NRWAL Equation Library. Default NRWAL Configs

Nunemaker, Jacob↗

A Communication Channel Density Estimating Generative Adversarial Network

Autoencoder-based communication systems use neural network channel models to backwardly propagate message reconstruction error gradients across an approximation of the physical communication channel. In this work, we develop and test a new generative adversarial network (GAN) architecture for the purpose of training a stochastic channel approximating neural network. In previous research, investigators have focused on additive white Gaussian noise (AWGN) channels and/or simplified Rayleigh fading channels, both of which are linear and have well defined analytic solutions. Given that training a neural network is computationally expensive, channel approximation networks— and more generally the autoencoder systems—should be evaluated in communication environments that are traditionally difficult. To that end, our investigation focuses on channels that contain a combination of non-linear amplifier distortion, pulse shape filtering, intersymbol interference, frequency-dependent group delay, multipath, and non-Gaussian statistics. Each of our models are trained without any prior knowledge of the channel. We show that the trained models have learned to generalize over an arbitrary amplifier drive level and constellation alphabet. We demonstrate the versatility of our GAN architecture by comparing the marginal probability density function of several channel simulations with that of their corresponding neural network approximations

Smith, Aaron↗

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

Signal Recognition↗

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

Signal Classification↗

Design and Discovery of N -(2-Methyl-5'-morpholino-6'-((tetrahydro-2 H -pyran-4-yl)oxy)-[3,3'-bipyridin]-5-yl)-3-(trifluoromethyl)benzamide (RAF709): A Potent, Selective, and Efficacious RAF Inhibitor Targeting RAS Mutant Cancers

RAS oncogenes have been implicated in >30% of human cancers, all representing high unmet medical need. The exquisite dependency on CRAF kinase in KRAS mutant tumors has been established in genetically engineered mouse models and human tumor cells. To date, many small molecule approaches are under investigation to target CRAF, yet kinase-selective and cellular potent inhibitors remain challenging to identify. Herein, we describe 14 (RAF709) [Aversa, Biaryl amide compounds as kinase inhibitors and their preparation. WO 2014151616, 2014], a selective B/C RAF inhibitor, which was developed through a hypothesis-driven approach focusing on drug-like properties. A key challenge encountered in the medicinal chemistry campaign was maintaining a balance between good solubility and potent cellular activity (suppression of pMEK and proliferation) in KRAS mutant tumor cell lines. We investigated the small molecule crystal structure of lead molecule 7 and hypothesized that disruption of the crystal packing would improve solubility, which led to a change from N-methylpyridone to a tetrahydropyranyl oxy-pyridine derivative. 14 proved to be soluble, kinase selective, and efficacious in a KRAS mutant xenograft model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lifetime predictions for dimmable two-channel drivers for color tuning luminaires

Two-channel tunable white lighting (TWL) systems represent the next wave of solid-state lighting (SSL) systems and promise flexibility in light environment while maintaining the high reliability and luminous efficacy expected with SSL devices. TWL systems utilize LED assemblies consisting of two different LED spectra (i.e., often a warm white assembly and a cool white assembly) that are integrated into modules. While these systems provide the ability to adjust the lighting spectrum to match the physiology needs of the task at hand, they also are a potentially more complex lighting system from a performance and reliability perspective. We report an initial study on the reliability performance of such lighting systems including an examination of the lumen maintenance and chromaticity stability of warm white and cool white LED assemblies and the multi-channel driver that provides power to the assemblies. Accelerated stress tests including operational bake tests conducted at 75°C and 95°C were used to age the LED modules, while more aggressive temperature and humidity tests were used for the drivers in this study. Small differences in the performance between the two LED assemblies were found and can be attributed to the different phosphor chemistries. The lumen maintenances of both LED assemblies were excellent. The warm white LED assemblies were found to shift slightly in the green color direction over time while the cool white LED assemblies shifted slightly in the yellow color direction. The net result of these chromaticity shifts is a small, barely perceptible reduction in the tuning range after 6,000 hours of exposure to an accelerating elevated temperature of 75°C.

Chromaticity↗

Leveraging accelerated testing of LED drivers to model the reliability of two-stage and multi-channel drivers

The next wave of LED lighting technology is likely to be tunable white lighting (TWL) devices which can adjust the colour of the emitted light between warm white (~ 2700 K) and cool white (~ 6500 K). This type of lighting system uses LED assemblies of two or more colours each controlled by separate driver channels that independently adjust the current levels to achieve the desired lighting colour. Drivers used in TWL devices are inherently more complex than those found in simple SSL devices, due to the number of electrical components in the driver required to achieve this level of control. The reliability of such lighting systems can only be studied using accelerated stress tests (AST) that accelerate the aging process to time frames that can be accommodated in laboratory testing. This paper describes AST methods and findings developed from AST data that provide insights into the lifetime of the main components of one-channel and multi-channel LED devices. The use of AST protocols to confirm product reliability is necessary to ensure that the technology can meet the performance and lifetime requirements of the intended application.

Davis, Lynn↗

An Assessment of the Economic Potential of Offshore Wind in the United States from 2015 to 2030

Output data from an NREL report entitled "An Assessment of the Economic Potential of Offshore Wind in the United States from 2015 to 2030" (NREL/TP-6A20-67675), which analyzes the spatial variation of levelized cost of energy (LCOE) and levelized avoided cost of energy (LACE) to understand the economic potential of fixed-bottom and floating offshore wind technologies across more than 7,000 U.S. coastal sites between 2015 and 2030.

17 WIND ENERGY↗

An Assessment of the Economic Potential of Offshore Wind in the United States from 2015 to 2030

This study describes an assessment of the spatial variation of levelized cost of energy (LCOE) and levelized avoided cost of energy to understand the economic viability of fixed-bottom and floating offshore wind technologies across major U.S. coastal areas between 2015 and 2030. In particular, this study offers insights into the available offshore wind resource by region at different levels of LCOE and an assessment of the economically viable resource capacity in the United States.

17 WIND ENERGY↗

NREL Offshore Balance-of-System Model

The U.S. Department of Energy (DOE) has investigated the potential for 20% of nationwide electricity demand to be generated from wind by 2030 and, more recently, 35% by 2050. Achieving this level of wind power generation may require the development and deployment of offshore wind technologies. DOE (2008) has indicated that reaching these 2030 and 2050 scenarios could result in approximately 10% and 20%, respectively, of wind energy generation to come from offshore resources. By the end of 2013, 6.5 gigawatts of offshore wind were installed globally. The first U.S. project, the Block Island Wind Farm off the coast of Rhode Island, has recently begun operations. One of the major reasons that offshore wind development in the United States is lagging behind global trends is the high capital expenditures required. An understanding of the costs and associated drivers of building a commercial-scale offshore wind plant in the United States will inform future research and help U.S. investors feel more confident in offshore wind development. In an effort to explain these costs, the National Renewable Energy Laboratory has developed the Offshore Balance-of-System model.

17 WIND ENERGY↗

Potential Offshore Wind Energy Areas in California: An Assessment of Locations, Technology, and Costs

This report summarizes a study of possible offshore wind energy locations, technologies, and levelized cost of energy in the state of California between 2015 and 2030. The study was funded by the U.S. Department of the Interior's Bureau of Ocean Energy Management (BOEM), the federal agency responsible for regulating renewable energy development on the Outer Continental Shelf. It is based on reference wind energy areas where representative technology and performance characteristics were evaluated. These reference areas were identified as sites that were suitable to represent offshore wind cost and technology based on physical site conditions, wind resource quality, known existing site use, and proximity to necessary infrastructure. The purpose of this study is to assist energy policy decision-making by state utilities, independent system operators, state government officials and policymakers, BOEM, and its key stakeholders. The report is not intended to serve as a prescreening exercise for possible future offshore wind development.

17 WIND ENERGY↗

Scenario analysis for techno-economic model development of U.S. offshore wind support structures

Challenging bathymetry and soil conditions of future US offshore wind power plants might promote the use of multimember, fixed-bottom structures (or 'jackets') in place of monopiles. Support structures affect costs associated with the balance of system and operation and maintenance. Understanding the link between these costs and the main environmental design drivers is crucial in the quest for a lower levelized cost of energy, and it is the main rationale for this work. Actual cost and engineering data are still scarce; hence, we evaluated a simplified engineering approach to tie key site and turbine parameters (e.g. water depth, wave height, tower-head mass, hub height and generator rating) to the overall support weight. A jacket-and-tower sizing tool, part of the National Renewable Energy Laboratory's system engineering software suite, was utilized to achieve mass-optimized support structures for 81 different configurations. This tool set provides preliminary sizing of all jacket components. Results showed reasonable agreement with the available industry data, and that the jacket mass is mainly driven by water depth, but hub height and tower-head mass become more influential at greater turbine ratings. A larger sensitivity of the structural mass to wave height and target eigenfrequency was observed for the deepest water conditions (>40 m). Thus, techno-economic analyses using this model should be based on accurate estimates of actual metocean conditions and turbine parameters especially for deep waters. Finally, the relationships derived from this study will inform National Renewable Energy Laboratory's offshore balance of system cost model, and they will be used to evaluate the impact of changes in technology on offshore wind lower levelized cost of energy.

17 WIND ENERGY↗

Expert elicitation survey on future wind energy costs

Wind energy supply has grown rapidly over the last decade. However, the long-term contribution of wind to future energy supply, and the degree to which policy support is necessary to motivate higher levels of deployment, depends - in part - on the future costs of both onshore and offshore wind. In this paper, we summarize the results of an expert elicitation survey of 163 of the world's foremost wind experts, aimed at better understanding future costs and technology advancement possibilities. Results suggest significant opportunities for cost reductions, but also underlying uncertainties. Under the median scenario, experts anticipate 24-30% reductions by 2030 and 35-41% reductions by 2050 across the three wind applications studied. Costs could be even lower: experts predict a 10% chance that reductions will be more than 40% by 2030 and more than 50% by 2050. Insights gained through expert elicitation complement other tools for evaluating cost-reduction potential, and help inform policy and planning, R & D and industry strategy.

17 WIND ENERGY↗