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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 73 records · Page 4

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

36 MATERIALS SCIENCE↗

Lightweight single-phase Al-based complex concentrated alloy with high specific strength

Developing light yet strong aluminum (Al)-based alloys has been attracting unremitting efforts due to the soaring demand for energy-efficient structural materials. However, this endeavor is impeded by the limited solubility of other lighter components in Al. Here, we propose to surmount this challenge by converting multiple brittle phases into a ductile solid solution in Al-based complex concentrated alloys (CCA) by applying high pressure and temperature. We successfully develop a face-centered cubic single-phase Al-based CCA, Al 55 Mg 35 Li 5 Zn 5 , with a low density of 2.40 g/cm 3 and a high specific yield strength of 344×10 3 N·m/kg (typically ~ 200×10 3 N·m/kg in conventional Al-based alloys). Our analysis reveals that formation of the single-phase CCA can be attributed to the decreased difference in atomic size and electronegativity between the solute elements and Al under high pressure, as well as the synergistic high entropy effect caused by high temperature and high pressure. The increase in strength originates mainly from high solid solution and nanoscale chemical fluctuations. Our findings could offer a viable route to explore lightweight single-phase CCAs in a vast composition-temperature-pressure space with enhanced mechanical properties.

42 ENGINEERING↗

A lightweight, user-configurable detector ASIC digital architecture with on-chip data compression for MHz X-ray coherent diffraction imaging

Today, most X-ray pixel detectors used at light sources transmit raw pixel data off the detector ASIC. With the availability of more advanced ASIC technology nodes for scientific application, more digital functionalities from the computing domains (e.g., compression) can be integrated directly into a detector ASIC to increase data velocity. In this paper, we describe a lightweight, user-configurable detector ASIC digital architecture with on-chip compression which can be implemented in 130 nm technologies in a reasonable area on the ASIC periphery. In addition, we present a design to efficiently handle the variable data from the stream of parallel compressors. The architecture includes user-selectable lossy and lossless compression blocks. The impact of lossy compression algorithms is evaluated on simulated and experimental X-ray ptychography datasets. This architecture is a practical approach to increase pixel detector frame rates towards the continuous 1 MHz regime for not only coherent imaging techniques such as ptychography, but also for other diffraction techniques at X-ray light sources.

47 OTHER INSTRUMENTATION↗

A New Shape Optimization Approach for Lightweighting Electric Machines Inspired by Additive Manufacturing

Minimizing the mass in electric machines while maintaining superior performance is a new requirement for the advancement of drivetrains used in wind energy and electric mobility. Topology optimization (TO) for lightweighting electric machines using traditional approaches typically explores a restricted design space allowed by standard parametrizable geometry and manufacturing, while advanced methods, such as cell-based density approaches, suffer from a lack of robust manufacturability constraints during the optimization process. To overcome these drawbacks, we explore a grid-independent, boundary optimization where the outer shape of the magnet is parameterized using Bezier curves. We conduct a design of experiments (DOE) to study the effect of different magnet shapes on machine performance by varying the control points on the Bezier curves. A machine-learning-based surrogate model is constructed using the data from the DOE to quantify the relationship between the control points, air-gap torque, and mass. The control points are then optimized to maximize the torque density. The approach is used for minimizing electrical steel mass in the International Energy Agency (IEA) 15-MW radial flux direct-drive wind turbine generator. The new approach to shape optimization resulted in smooth and concise shapes that can be easily additively manufactured with up to a 20-ton reduction in electrical steel mass.

additive manufacturing↗

Lightweight LSTM for CAN Signal Decoding

This paper describes an approach to identify undecoded Controller Area Network (CAN) data from one vehicle, based on the data similarity to previously decoded CAN data from another vehicle. Modern vehicles communicate data and signals from on-board sensors and controllers through the CAN bus. Networked sensors contain information such as wheel speeds, fuel gauges, turn signals, and radar signals. In the effort to use this information and make cars safer through human-in-the-loop CPS, signals on the CAN bus such as wheel speed and radar can be used to support the driver. However, data from the CAN bus are encoded and in some cases compressed, and different car manufacturers use different encoding schemes to represent data on the CAN bus. With hundreds of messages and thousands of possible encoding schemes to consider, it is laborious to identify the unique bits and encoding schemes that represent signals on each vehicle. In this study, we propose a method for training a Long Short-Term Memory (LSTM) neural network on known radar signals from one vehicle manufacturer, a Toyota, and successfully apply the network to identify the encoding for radar signals on a different vehicle, a Honda. By augmenting the training dataset with varied encoding bit boundaries, a small and lightweight LSTM network can learn to recognize radar data across different encoding schemes. The results are an improvement on exhaustive-search algorithms and other methods previously used in the search for such signals.

Ngo, Paul↗

BinaryCIF and CIFTools—Lightweight, efficient and extensible macromolecular data management

3D macromolecular structural data is growing ever more complex and plentiful in the wake of substantive advances in experimental and computational structure determination methods including macromolecular crystallography, cryo-electron microscopy, and integrative methods. Efficient means of working with 3D macromolecular structural data for archiving, analyses, and visualization are central to facilitating interoperability and reusability in compliance with the FAIR Principles. We address two challenges posed by growth in data size and complexity. First, data size is reduced by bespoke compression techniques. Second, complexity is managed through improved software tooling and fully leveraging available data dictionary schemas. To this end, we introduce BinaryCIF, a serialization of Crystallographic Information File (CIF) format files that maintains full compatibility to related data schemas, such as PDBx/mmCIF, while reducing file sizes by more than a factor of two versus gzip compressed CIF files. Moreover, for the largest structures, BinaryCIF provides even better compression—factor ten and four versus CIF files and gzipped CIF files, respectively. Herein, we describe CIFTools, a set of libraries in Java and TypeScript for generic and typed handling of CIF and BinaryCIF files. Together, BinaryCIF and CIFTools enable lightweight, efficient, and extensible handling of 3D macromolecular structural data.

59 BASIC BIOLOGICAL SCIENCES↗

Novel Lightweight, Low-Cost Heliostat for Concentrating Solar Power (SBIR Phase I Final Report)

The overall goal of this Department of Energy (DOE) SBIR Phase I project was to demonstrate the feasibility of the L.Garde, Inc. heliostat mirror facet for use in concentrated solar power applications. Prior to this Phase I project, L.Garde, Inc. developed a design for a lightweight and low cost mirror facet and successfully fabricated small scale (0.667 m 2 ) with a mirror surface flatness of 0.7 mrad. Therefore, the focus of the Phase I effort was to (1) demonstrate scalability by fabricating larger size mirrors while retaining the same mirror surface flatness, (2) demonstrate the design can withstand operating environment conditions through field testing, and (3) perform cost analysis to show the heliostat mirror facet design can meet DoE goals of < 12 kg/m2 and <$30/m 2 . During the Phase I project, L.Garde successfully fabricated large area (1.395 m 2 ) heliostat mirror facets, with a mass per unit area of 8 kg/m 2 and a cost of $29.80/m 2 . Surface flatness measurements (using contact probe technique) were performed on the mirror surface and results showed a flatness of 0.68 mrad, which were in agreement with previously fabricated small scale mirror facets. Slope error measurements was also performed on the mirror surface and results showed a slope error of 0.77 mrad which also was in agreement with previously fabricated small scale mirror facets. One large area mirror facet was subjected to a three (3) month field test. Surface flatness and slope error measurements were performed on the mirror surface after the field test and results were 0.663 mrad and 0.58 mrad respectively. The large scale heliostat mirror facets were also subjected to accelerated aging. However, during this exposure we observed failure due to the breaking of the mirror facets. Further investigation into the source of the failure showed that the mirror component alone showed signs of degradation during the same accelerated aging test. We believe that moisture ingress is occurring when subjected to high humidity, leading to buildup of water with the layers of protective paints and resulting in mirror breakage when water expands in freezing conditions. In order to mitigate or eliminate this issue, a new weatherproofing strategy may be implemented or a new mirror component may be used that is able to survive accelerated aging conditions.

14 SOLAR ENERGY↗

Optimized Carbon Fiber Intermediate Development to Enable High-Volume Manufacturing of Lightweight Automotive Composites

The ongoing pursuit of improved fuel economy and reduced greenhouse gas emissions has resulted in sustained interest for lightweight materials technologies. In this context, carbon fiber composites have captured the imagination of automotive engineers due to the potential to achieve substantial mass reduction when compared to traditional steel construction. That stated, the use of carbon fiber composites in automotive has been limited for the most part to premium supercars and other derivative platforms. In these cases, manufacturing costs are less of an obstacle to implementation, and the performance benefits of carbon fiber have enabled production of structures offering more than 50% weight savings. In practice, translating these low-volume demonstrations onto high-volume vehicle platforms has remained challenging. This can be attributed to several factors, with the absence of suitable high throughput production methodologies being a key impediment. To date, structural, crash critical components have relied upon manufacturing techniques born out of the aerospace industry. This has created a disconnect between automotive production systems that are accustomed to manufacturing multiple parts per minute and the aerospace technologies that have cycle times in the order of hours. Consequently, the focus of this project is the development of manufacturing process technology for carbon fiber composites that can support a mainstream vehicle program at an assumed throughput of 100,000 vehicles per year. In practice, this translates to a part-to-part cycle time of less than 3 minutes. Project participation included contributions from a broad range of academic, industrial and national lab partners. The primary scope of work, being the development of new carbon fiber epoxy compounds that are stable at room temperature and suited to high throughput automated processing. For project management, the work streams were divided into six key areas, with the lead organization in parentheses. • Carbon fiber/epoxy materials formulation development and scale up (Dow) • Simulation of discontinuous near isotropic meso-structure intermediates (Purdue) • Simulation of mechanical performance of compression molded components (Purdue) • Meso-Scale morphological analysis and correlation with structural performance (UTK) • Paint and adhesion durability analysis (MSU) • Demonstrator part design, prototype production, and validation testing (Ford). The primary goal at the commencement of the project was development of a chopped carbon fiber sheet molding compound (SMC) that offered a three times improvement in tensile modulus over a comparable glass-based SMC. In addition to meeting mechanical performance targets, the resin kinetics were modified to achieve a processing cycle time of less than 3 minutes. Other critical-to-quality (CTQ) specifications were also stipulated to account for a broad range of materials and processing characteristics. To achieve the above, staff scientists at Dow Chemical created an extensive series of new epoxy blends for testing and validation. Throughout this development, a key challenge was attaining material performance goals without impacting processing behavior and paintability of finished components. The latter required a new internal mold release system being developed by Dow that was designed to complement the kinetics of the rapid cure epoxy. As a complement to work studies at the industrial partners, the teams from academia executed a series of analytical and experimental studies to investigate potential factors influencing CF-SMC performance. Unit cell models were developed to capture the meso-scale representations of the fiber matrix architecture. Results of this analysis and subsequent morphological investigations led to the design of a novel composite derivative comprising carbon fiber platelets embedded in an epoxy matrix; the platelet size and aspect ratio playing significant role in final composite properties. This approach was a departure from previous research in CF-SMC development whereby bulk filamentization or disassembly of the carbon fiber rovings had been considered the most effective means of achieving both fiber wet through and wet-out. As the course of the academia studies progressed, the aspect ratio of the fiber constituents was further optimized before finalizing material attributes and processing conditions. For the purposes of technology validation, the Ford team led a work stream devoted to the design, fabrication and testing of demonstration components. The carbon fiber SMC material has the potential to displace numerous stampings and castings on an automotive structure but ultimately vehicle closure applications were selected to showcase the abilities of the CF-SMC to achieve both mass reduction and business case for large complex structures. Using target properties established by the Dow staff scientists, the complete closure system for a full-size sedan decklid and a mid-size wagon liftgate were engineered. Prototypes for both applications were fabricated using production representative processing methods to allow for physical testing and performance validation of the CF-SMC structures. Following completion of a testing program that concluded with a FMVSS301 55 mph offset rear crash, the CF-SMC formulation was declared by the Ford team to have met all engineering requirements. To summarize, the joint development activities during this project led to significant technical breakthroughs and achievement of all milestones. The result was the development of a novel, tack-free carbon fiber molding compound that is suited to automated processing. This combined room temperature stability, fast cure kinetics, and internal mold release system facilitates cycle times that are conducive to high-volume production. The VORAFUSE M6400 successfully passed technology validation at Ford and is now eligible for consideration on future production commercial vehicle programs.

36 MATERIALS SCIENCE↗

Highly Recyclable Thermosets for Lightweight Composites: CRADA 517 [Abstract only]

Lightweight composites are of increasing need to enable reduced fuel usage, reduced carbon emissions and increased range in air and ground transportation. The superior weight savings of carbon fiber thermoset composites are impeded by material and production costs and the limited options available for composite repair and recycle. The materials recovery and recycling sector is currently overwhelmed by an abundance of low-value materials and limited market opportunities for downcycled content, rendering landfilling a more attractive alternative. Vitrimers represent a new paradigm for repairable and recyclable thermosets, but this relatively new technology will require development, including government investment, to reduce risks for its adoption by aerospace and automotive OEMs. The overall goal of the project is to create recyclable carbon fiber composites using vitrimer resins that are more energy efficient to produce and have improved properties over baseline technology. The targeted composites will retain their tensile strength after multiple recycling and reprocessing steps. In addition, monomer will be recoverable through depolymerization and re-usable carbon fibers will be retrieved.

36 MATERIALS SCIENCE↗

Hydrophobic, Thermal-shock Resistant Lightweight Cement Composites in Hybrid Thermal Energy-Storage Geothermal Well System

Under the DOE EERE Geothermal Technology Office (GTO)-funded project in FY 2019-2022, Brookhaven National Laboratory (BNL) aimed to develop hydrophobic thermal-shock resistant lightweight well cement composites suitable for temporarily storing a curtailed hot working fluid incurred from excess geothermal-, solar-, and wind-generated energies in underground reservoirs thermal energy storage sites. This storage energy systems are designed to provide energy during the periods between energy-harvesting and -requiring periods. One key factor to the success of this project was hydrophobicity of cement composites. The hydrophobic composites not only upgrade thermal insulating properties of water-saturated composites for minimizing heat loss in upper well surface regions, but also provide improved mechanical properties related to thermal-shock resistance and the protection of carbon steel (CS) casing against corrosion.

15 GEOTHERMAL ENERGY↗

Accelerating Manufacturing of Powder-Processed Strong, Lightweight and Thermally Stable Bulk Nanocrystalline Al Alloys via Engineered Interface States

The overarching goal of this program is to develop an integrated materials by design framework enabling a simple, scalable, and efficient manufacturing route for thermally stable nanocrystalline Al-based alloys with high specific strength over a range of service temperatures. The central scientific principle underpinning this program is the elucidation, and ultimately implementation in novel alloy design, of unique interfacial structures and chemistries driven by segregation in multi-component systems that give rise to unprecedented processability and properties. This program targeted nanocrystalline Al-based ternary alloys produced by mechanical alloying of powders followed by compaction and sintering with hot pressing, which are inherently scalable and inexpensive manufacturing routes, but when applied to nanocrystalline alloys are usually plagued by low density and/or poor retention of the intended nanostructures during processing. This program successfully demonstrated manufacturing of a bulk (>1 cm 3 ) nanocrystalline Al-based alloy with a combination of thermal stability, high temperature strength retention, and specific strength that exceeds the current-state-of-the-art of Al alloys. It is anticipated that the greatest technological impact will occur by demonstration of rapid and scalable manufacturing of bulk nanocrystalline Al alloys with exceptional thermal stability and mechanical performance, thus enabling increased energy efficiency in high performance power generation systems via: (i) replacement of existing components with lightweight Al-based alloys and (ii) increasing operating temperatures with property retention. The program focused on the development of a simple and efficient manufacturing route for thermally stable nanocrystalline Al-based alloys with high specific strength over a range of service temperatures. The program is expected to have direct impact on scalable and economic manufacturing of bulk nanocrystalline alloys. This program profited from the recent discovery by the project team of segregation-driven amorphous intergranular films in nanocrystalline metallic alloys that can be kinetically frozen-in at sub-solidus temperatures. These interfacial states (also known as amorphous complexions) comprise a large fraction of the total material in nanocrystalline alloys and are responsible for two beneficial characteristics that anchor the proposed work: (1) activated sintering leading to high density and (2) retained nanostructures leading to high strengths that approach a substantial fraction of the theoretical limit. More specifically, these engineered interfaces led to a three-fold benefit: (i) high-throughput materials processing with low energy budget and cost, (ii) exceptional thermal stability, and (iii) high specific strength at both room temperature and intermediate temperatures experienced during service.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hydrophobic, Thermal-shock Resistant Lightweight Cement Composites in Hybrid Thermal Energy-Storage Geothermal Well System

Under the DOE EERE Geothermal Technology Office (GTO)-funded project in FY 2019-2022, Brookhaven National Laboratory (BNL) aimed to develop hydrophobic thermal-shock resistant lightweight well cement composites suitable for temporarily storing a curtailed hot working fluid incurred from excess geothermal-, solar-, and wind-generated energies in underground reservoirs thermal energy storage sites. This storage energy systems are designed to provide energy during the periods between energy-harvesting and -requiring periods.

15 GEOTHERMAL ENERGY↗

Additively Manufactured, Lightweight, Low-Cost Composite Vessels for Compressed Natural Gas Fuel Storage

This project will develop a process to combine AM via direct ink writing (DIW) technology for CFC printing and to use design optimization tools pioneered at LLNL, with advances in resin/composite formulation enabled by chemical and nano-material modification to produce lightweight low-cost CNG tanks. Our approach will yield sub-scale prototype composite pressure tanks equivalent to Type-5 CNG vessel designs that demonstrate a potential cost-benefit advantage. Central to our vision is using agile AM and design based on computationally informed DIW of both short and continuous CF, further coupled with high-performance thermoset polymer matrixes modified by emergent nanomaterials. Our single-stage, multi-material AM technology, combined with a decreased volume fraction of CF and an increased proportion of economically advantaged short fiber, all together drive the reduction in manufacturing time and overall cost. Importantly, reductions in continuous fiber and overall fiber volume fraction will be achieved without detriment to the mechanical strength of the composite vessel. This will be achieved by employing a single process using multi materials grading involving a thermoset resin “ink” modified with aligned nanoplatelets to leverage the efficient tortuous-path gas barrier effect, printed as an inner flexible gas barrier as the initial stage in our manufacturing process before compositionally grading the AM feedstock in real-time to transition to a rigid, structural CF-filled resin. The proposed hybrid construction is projected to achieve pressure ratings at a service range of 2,900–3,600 psi with a 3× burst safety factor comparable to conventional filament-wound composite tanks with an estimated 30–50% reduction in total manufacturing cost.

03 NATURAL GAS↗

Enabling Next Generation Reaction Injection Molding (RIM) for Lightweight Structures

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this project, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. This optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption. This research has been performed in collaborations with McClarin Composites. The research outcome has been submitted to the Journal of Manufacturing Processes.

36 MATERIALS SCIENCE↗

Lightweight Metal Stamping Optimization Enabled by Artificial Intelligence

Successfully manufacturing an automotive body structure made via the sheet metal stamping process depends upon simultaneous consideration of component design, tooling design, stamping process control, and material properties. In many cases, introducing lightweight sheet materials (e.g., aluminum alloys, magnesium alloys, advanced high strength steels) holds the potential to significantly reduce vehicle weight, but challenges the stamping process by introducing materials with inherently less ductility. Successful and repeatable applications require co-developing the stamping process controls with the varying material properties, including formability. During the stamping process, as soon as the forming limit of the sheet is exceeded, the material shows localized necking which quickly leads to splits. Controlling process variability to avoid these material splits will enable deployment of less formable, lighter, and stronger materials for stamped automotive components. A typical optimization procedure for manufacturing requires an iterative process involving parameter setting, execution of computational simulations, and modifying the parameters. The entire process demands substantial computational time, making it impractical for real-time feedback towards rapid corrective actions required for in-line control for running production processes. To overcome this challenge, artificial intelligence (AI) can be leveraged to determine optimal manufacturing parameters within a single manufacturing cycle time. This research proposes an in-line optimization framework incorporating a trained AI model to predict kidney-shaped die forming. Preliminary results indicate that the AI framework can accurately predict draw-in values based on a given parameter set, a process referred to as forward prediction. Furthermore, the AI framework can also predict the optimal parameter set that leads to the desired draw-in values, referred to as inverse optimization (or backward prediction). This research has been performed in collaborations with USCAR (US Council for Automotive Research) and AutoForm. The members of USCAR are Ford, GM, and Stellantis.

36 MATERIALS SCIENCE↗

Highly Recyclable Thermosets for Lightweight Composites

The objective of this project, Highly Recyclable Thermosets for Lightweight Composites (DOE Award DE-EE0009297), was to develop recyclable carbon fiber–reinforced polymer (CFRP) composites that are more energy efficient to produce than existing technologies while achieving superior mechanical performance and enabling closed-loop material recovery. Specifically, the project targeted vitrimer-based composites with tensile strength at least 20% higher than baseline recyclable polypropylene composites, retention of greater than 95% of tensile strength after multiple recycling and reprocessing cycles, recovery of carbonate monomers through depolymerization, and recovery of greater than 95% of carbon fibers of reusable quality. The project was carried out by The University of Akron in collaboration with Pacific Northwest National Laboratory and Raytheon Technologies Research Center.

36 MATERIALS SCIENCE↗

Modal Analysis of Ultrasonic Spot Welding for Lightweight Metals Joining

Ultrasonic spot welding (USW) represents one of the unique solid-state joining methods for lightweight materials such as magnesium alloy and aluminum alloy. However, the sonotrode vibration may have a detrimental impact on the sheet material and the existing welds, depending on the component geometry and vibration frequency. In this study, a modal analysis tool based on steady-state dynamics was developed for ultrasonic spot welding which features a cyclic load applied to the sheets during the joining process. Through predicting relative motion and shear stress at the faying surfaces, coupon geometry and weld spacing are identified as two major factors that affect the welding reliability and joint quality in USW. The model was validated via welding experiments on aluminum alloy and magnesium alloy and relevant characterization of temperature distribution, joint strength as well as fracture location.

36 MATERIALS SCIENCE↗

Optimization of a Lightweight Floating Offshore Wind Turbine with Water Ballast Motion Mitigation Technology

Floating offshore wind turbines are a promising technology for addressing energy needs by utilizing wind resources offshore. The current state of the art is based on heavy, expensive platforms to survive the ocean environment. Typical design techniques do not involve optimization because of the computationally expensive time domain solvers used to model motions and loads in the ocean environment. However, this design uses an efficient frequency domain solver with a genetic algorithm to rapidly optimize the design of a novel floating wind turbine concept. The concept utilizes a liquid ballast mass to mitigate motions on a lightweight post-tensioned concrete platform. The simple cruciform-shaped design of the platform made of post-tensioned concrete is less expensive than steel, reducing the raw material and manufacturing cost. The use of ballast water to behave as a tuned mass damper allows a smaller platform to achieve the same motions as a much larger platform, thus reducing the mass and cost. The optimization techniques applied with these design innovations resulted in a design with a levelized cost of energy of USD 0.0753/kWh, roughly half the cost of the current state of the art.

Ramsay, William↗