Search NASA⌕ Search

SEARCH · Search NASA

Results for “Additive construction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

Urban Traveler - Changes and Impacts: Mobility Energy Productivity (MEP) Metric

For nearly a century, the automobile has been the primary mode of personal transportation in American life. This remains true today as millions of people rely heavily on cars to connect suburbs with cities or to travel long distances—often out of routine or convenience. However, advances in technology are fueling an era of transportation transformation, with the potential to transform a system that has remained virtually unchanged for decades. Aspiring smart cities are wrestling with questions such as: How does mobility impact a person’s quality of life? Would people make different travel choices if they were presented with better information about their mobility options? The ability to quantify the mobility potential of a given location is the first step toward answering these questions. In response, an interdisciplinary team at the National Renewable Energy Laboratory (NREL) has developed the Mobility-Energy Productivity (MEP) metric. The MEP metric provides an avenue to not only measure the mobility potential at a specific location in its current configuration, but also to test how various technological advances (e.g., connected and automated vehicles, plug-in electric vehicles, shared mobility) and infrastructure investments (e.g., building an additional highway lane, constructing a new shopping mall, implementing a transit-oriented development) impact the mobility of that location over time. This presentation details the FY19 progress on the MEP metric project funded through DOE VTO's SMART Mobility Consortium.

47 OTHER INSTRUMENTATION↗

Machine Learning for Automated Extraction of Building Geometry

As data science comes to buildings, the promise of using machine learning and novel sources of data has received much attention. Advances in machine learning and computer vision algorithms, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics – cost-effectively, and at scale. Acquisition of features such as footprint are time consuming and costly to acquire with today’s manual methods, but can be streamlined through intelligent software-based solutions applied to satellite images. When combined with aerial RGB and thermal images, full 3D geometries and thermal maps can be constructed to determine additional characteristics such as window to wall ratio, height, number of stories and envelope thermal characteristics. In this paper we present three contributions to accelerate these high potential opportunities: (1) a methodical analysis of how these features can be integrated into today’s simulation and data driven software tools to enhance efficiency measure identification and owner/operator decision making; (2) development and accuracy testing of open source deep neural network methods to extract building footprints from satellite imagery, including the curation and application of openly available GIS datasets for training and continued development by others; and (3) an open framework for drone-based image capture and creation of 3D building geometries. This work represents an important bridge between high-level studies that span diverse application areas and those that detail point solutions yet cannot be easily replicated or extended.

Touzani, Samir↗

Polypeptide and yeast cell compositions and methods of using the same

Polypeptides comprising maltose/maltotriose transporters are provided. Additionally, polynucleotides, DNA constructs, and vectors encoding a maltose/maltotriose transporter, or yeast cells harboring such polynucleotides are provided. The yeast cell may be a Saccharomyces eubayanus cell modified to increase the expression or transport activity of a maltose/maltotriose transporter at the plasma membrane of the cell. Further, methods are provided for making a fermentation product by culturing any one of the yeast cells described herein with a fermentable substrate. Finally, methods are provided to select for and isolate maltotriose-utilizing strains of Saccharomyces eubayanus.

Hittinger, Chris Todd↗

Polypeptide and yeast cell compositions and methods of using the same

Polypeptides comprising maltose/maltotriose transporters are provided. Additionally, polynucleotides, DNA constructs, and vectors encoding a maltose/maltotriose transporter, or yeast cells harboring such polynucleotides are provided. The yeast cell may be a Saccharomyces eubayanus cell modified to increase the expression or transport activity of a maltose/maltotriose transporter at the plasma membrane of the cell. Further, methods are provided for making a fermentation product by culturing any one of the yeast cells described herein with a fermentable substrate. Finally, methods are provided to select for and isolate maltotriose-utilizing strains of Saccharomyces eubayanus .

Hittinger, Chris Todd↗

Increasing Main Cooler Thermal Performance for sCO2 Power Cycles

Increasing sCO2 power cycle cooler performance will increase the efficiency and lower the cost of electricity for sCO2 power cycles. This work considered the heat transfer performance of two counter-flow, shell-and-tube heat exchangers using local measurements. The heat exchangers were constructed using commercial tubing. One heat exchanger was constructed with a conventional, smooth inner tube (7 mm nominal inner diameter). The other was constructed with an additively manufactured tube with a square cross section and angled rib turbulators. For mixed mean temperatures away from the pseudocritical temperature, the heat transfer coefficient matched the Dittus-Boelter correlation. As the mixed mean temperature approached the pseudocritical temperature, the heat transfer coefficient deviated from the Dittus-Boelter correlation due to transverse property variation and buoyancy. The local and average heat transfer coefficients for angled rib tubes were nominally 150% to 300% greater than the heat transfer coefficients for the smooth tube. Trends in heat exchanger effectiveness indicated that the ribs were most beneficial when the water flow rates were at the low end of the range considered: 0.016 – 0.126 kg/s. Using results from prior system modeling, it is anticipated that adding heat transfer enhancement features in a cycle cooler will increase the sCO2 cycle efficiency by 0.34 percentage points.

Searle, Matthew↗

Increasing Main Cooler Thermal Performance for sCO2 Power Cycles

Increasing sCO2 power cycle cooler performance will increase the efficiency and lower the cost of electricity for sCO2 power cycles. This work considered the heat transfer performance of two counter-flow, shell-and-tube heat exchangers using local measurements. The heat exchangers were constructed using commercial tubing. One heat exchanger was constructed with a conventional, smooth inner tube (7 mm nominal inner diameter). The other was constructed with an additively manufactured tube with a square cross section and angled rib turbulators. For the present study, the measured Nusselt number was 30% less than the Dittus-Boelter correlation. The decrease was attributed to heat transfer degradation. The cooler performance was also reported as heat exchanger effectiveness. A factor of two improvement in Nusselt number (94%) relative to smooth conventional tubes was observed, indicating that heat transfer enhancement features (such as the ribs) are a suitable technology to overcome heat transfer degradation in sCO2 coolers. Trends in heat exchanger effectiveness indicated that the ribs were most beneficial when the water flow rates were at the low end of the range considered: 0.016 – 0.126 kg/s. Using results from prior system modeling, it is anticipated that adding heat transfer enhancement features in a cycle cooler will increase the sCO2 cycle efficiency by 0.34 percentage points.

Searle, Matthew↗

Additive-Induced Morphology Change of Polymer Film Enables Enhanced Charge Mobility and Faster Organic Electrochemical Transistor Switching

Conjugated polymers (CPs) play an important role in organic electrochemical transistors (OECTs) for bioelectronics and related applications, where they serve as channel materials. Currently, most successful polymers for CPs are re-engineered from traditional CPs by replacing hydrophobic alkyl side chains with hydrophilic ethylene glycol or ionic groups. Frustratingly, the enhanced ion transport often compromises the charge mobility of the original CP. In this work, we present an additive-mediated method to construct a modified poly(3-hexylthiophene) (P3HT) film to enable efficient ion migration. The additive is designed with a cleavable diazo group that releases nitrogen and 2-methoxyethanol, a volatile compound, to alter the P3HT film morphology. OECTs based on the film exhibit improved response times. Interestingly, the process also enhances the crystallinity of P3HT, leading to higher hole mobility compared with pristine P3HT. This study proposes an in situ strategy to achieve the functionality of the OMIEC via morphological regulation, offering a promising route to simultaneously enhance both ion accessibility and charge mobility.

Organic polymers↗

Interfaces and the extended Hilbert space of Chern-Simons theory

The low energy effective field theories of (2 + 1) dimensional topological phases of matter provide powerful avenues for investigating entanglement in their ground states. In [1] the entanglement between distinct Abelian topological phases was investigated through Abelian Chern-Simons theories equipped with a set of topological boundary conditions (TBCs). In the present paper we extend the notion of a TBC to non-Abelian Chern-Simons theories, providing an effective description for a class of gapped interfaces across non-Abelian topological phases. These boundary conditions furnish a defining relation for the extended Hilbert space of the quantum theory and allow the calculation of entanglement directly in the gauge theory. Because we allow for trivial interfaces, this includes a generic construction of the extended Hilbert space in any (compact) Chern-Simons theory quantized on a Riemann surface. Additionally, this provides a constructive and principled definition for the Hilbert space of effective ground states of gapped phases of matter glued along gapped interfaces. Lastly, we describe a generalized notion of surgery, adding a powerful tool from topological field theory to the gapped interface toolbox.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hybrid Curve Fitting For Reducing Motion Commands In Object Construction

Existing slicing software for additive manufacturing typically requires a triangulated mesh as its input. Triangulated meshes are approximate representations of exact CAD models. Despite the loss in dimensional accuracy, triangulated meshes are used because they are computationally easier to cross-section and offset than the exact geometry in CAD format. When a triangulated object is prepared, the resulting machine instructions include only linear motion commands. Numerous modern motion controllers can move in arc and spline motions; however, the absence of slicing software that supports curvature prevents these commands from being leveraged. To address this limitation, this paper presents a method for the hybrid reconstruction of arcs and splines as a post-processing step to traditional slicing. This method can greatly reduce the number of motion commands required to construct an object by printing smooth curved surfaces. This concise representation of tool-pathing allows for more even extrusion and is computed without a major impact on slicing time.

Wade, Charles↗

A cosine-based correlation information entropy approach for building automatic fault detection baseline construction

Building automatic fault detection and diagnosis (AFDD) technologies have shown great potential for energy savings. To enable AFDD, a baseline depicting the normal operation mode is needed to detect whether the building operation deviates from normality. Existing research using physics-based knowledge and models for AFDD has mainly taken a trial-and-error approach to determine if a given baseline is sufficient via empirical experiments. A mechanism to support decisions such as how many samples and what samples should be included in the baseline is currently lacking. In this study, a data-driven method for AFDD baseline construction based on information entropy is developed. The entropy is derived based on cosine similarity among typical building automation system measurements in conjunction with outdoor weather information. The performance of the proposed method is evaluated using real building data. Evaluation results indicate that the fault detection strategy adopting the proposed method has similar or better accuracy in detecting faults compared to the same fault detection strategy using the baseline construction method from the literature. Additionally, the use of entropy enables the proposed method to automatically construct and assess the baseline consisting of information-rich samples.

42 ENGINEERING↗

Indirect additive manufacturing process for producing SiC—B4C—Si composites

A method for indirect additive manufacturing of an object constructed of boron carbide, silicon carbide, and free silicon, comprising: (i) producing a porous preform constructed of boron carbide and silicon carbide by an indirect ceramic additive manufacturing (ICAM) process in which particles of a powder mixture become bonded together with an organic binder, wherein the powder mixture comprises: a) boron carbide particles, and b) silicon carbide particles, wherein at least 80 vol % of the silicon carbide particles are larger than the boron carbide particles; and wherein the boron carbide and silicon carbide particles are each included in an amount of 40-60 wt. % of the powder mixture, provided that the foregoing amounts sum to at least 95 wt. %; (ii) subjecting the porous preform to a temperature of 500-900° C. to volatilize the organic binder; and (iii) infiltrating molten silicon into pores of the porous preform to produce the object.

Cramer, Corson L.↗

Storm DEPART(Damage Estimate Prediction And Recovery Tool)

Damage prediction, materials needed, and resource allocation modeling capability in order to support pre-incident planning and preparation by predicting damage to the power generation capacity, transmission grids, distribution networks, and communications assets. The capabilities will be developed by multiple factors to include wind bands, storm surge, and flooding forecasts to participant’s assets which will result in a report of predicted damages. Additional factors to include available participants infrastructure data to include class, age, construction, location, wind rating, and additional information not in the public domain. Based on predicted damages, the output will be a bill of materials (BOM) to support short-term recovery operations. The extensiveness and level of detail for this BOM will depend on the replacement configuration specifications provided for each individual participant asset. Any limiting factors for the model will be applied related supply chain and resource constraints.

Klett, Mary↗

Characterization of Refractory Alloys Produced by Laser Additive Manufacturing

Refractory alloys often possess superior thermomechanical properties compared to conventional materials, such as steels, Ni-based superalloys, and Ti alloys, especially in high-temperature environments. While these materials promise to revolutionize numerous industries, significant hurdles remain for insertion into applications due to an incomplete understanding of structure-property relationships and conventional processing challenges. We explore laser-based additive manufacturing (AM) to construct refractory alloys consisting of combinations of Mo, Nb, Ta, and Ti with systematically increasing compositional complexity. Microstructure, composition, and hardness of the AM-processed alloys were characterized. Results are discussed in the context of pairing additive manufacturing with refractory metals to enable next-generation alloys.

Kustas, Andrew B.↗

A reinforcement learning approach to long-horizon operations, health, and maintenance supervisory control of advanced energy systems

In this work, we develop a Reinforcement Learning (RL) approach to the supervisory control problem for advanced energy systems, such as novel nuclear reactors and other demand-driven, mission-critical, and component-health-sensitive energy plants. The inclusive problem landscape considered captures the stochastic confluence of plant performance, component health evolution, power demand from the grid, diverse maintenance actions, and operator-defined goals and constraints, all considered over meaningfully long-enough reasoning horizons. Key aspects of the proposed approach are a receding horizon control-inspired technique dictating time- or event-triggered supervisory policy (re-)constructions, as well as additional capability-enabling contributions such as timescale compression, to handle long reasoning horizons and uncertainty in parts of the problem, and practical yet demonstrably-effective handling of hybrid action spaces with continuous and discrete decision variables. The resulting algorithm consists of a simulation-based RL agent constructing stochastic supervisory control policies over nontrivial action spaces and for long horizons, applying the learned policy to the system for a much shorter interval, and perpetually repeating, to construct the next long-horizon policy. That next policy will only be applied, again, for a short interval, yet originally far-in-time events move progressively closer, their associated uncertainty decreases, and new events and aspects enter the reasoning horizon. The proposed methodology bridges fundamental receding horizon concepts with the unequivocally stronger and more scalable reasoning of contemporary RL. Numerical examples using Soft Actor–Critic Deep RL illustrate the operation and efficacy of the proposed technique for a power plant tasked with health-aware load following missions in a dynamic electricity market landscape.

97 MATHEMATICS AND COMPUTING↗

Metamodels for Rapid Analysis of Large Sets of Building Designs for Robotic Constructability: Technology Demonstration Using the NASA 3D Printed Mars Habitat Challenge

Disruptive robotic construction technologies such as additive deposition of cementitious materials like concrete (or "3D concrete printing") require the synchronous operation of multiple pieces of equipment in the production setup. In such an environment, it is crucial to simulate the robotic motions (for toolpath clashes) and the cementitious material behavior (for toolpath failures) to ensure fail-proof constructability of the envisioned building geometry. However, toolpath clash detection requires 4D simulations of the production setup, which are computationally graphics intensive, whereas toolpath failure detection requires actual 3D printing of test parts from the geometry to identify areas prone to failure while 3D printing, which is physically tedious. Both these processes, being computationally and physically intensive, have largely curtailed designers from simulating and exploring large sets of design options with varying geometries and toolpath configurations. To overcome this and allow designers to explore large sets of design possibilities, this paper proposes two novel computational metamodels capable of performing robotic toolpath clash detection and failure detection with significantly reduced times than the earlier approaches. The developed metamodels were used to rapidly simulate large sets of building design options for robotic constructability in the NASA 3D-Printed Mars Habitat Challenge.

clash detection↗

Partial fillings of the bosonic $E$ 8 quantum Hall state

Here, we study bosonic topological phases constructed from electrons. In addition to a bulk excitation energy gap, these bosonic phases also have a fermion energy gap, below which all local excitations in the bulk and on the edge are even combinations of electrons. We focus on chiral phases, in which all low-energy edge excitations move in the same direction, that arise from the short-range entangled $E_8$ quantum Hall state, the bosonic analog of the filled lowest Landau level of electrons. The $E_8$ edge-state theory features an $E_8$ Kac-Moody symmetry that can be decomposed into ${\cal G}_A \times {\cal G}_B$ subalgebras, such as $SU(3) \times E_6$, $SO(M) \times SO(16-M)$, and $G_2 \times F_4$. (Here, $\{SO(M) \}$, $\{SU(N)\}$, and $\{E_8, G_2, F_4 \}$ denote orthogonal, unitary, and exceptional Lie algebras.) Using these symmetry decompositions, we construct exactly solvable coupled-wire model Hamiltonians for families of long-range entangled ${\cal G}_A$ or ${\cal G}_B$ bosonic fractional quantum Hall states that "partially fill" the $E_8$ state and are pairwise related by a generalized particle-hole symmetry. These long-range entangled states feature either Abelian or non-Abelian topological order. Some support the emergence of non-local Dirac and Majorana fermions, Ising anyons, metaplectic anyons, Fibonacci anyons, as well as deconfined $\mathbb{Z}_2$ gauge fluxes and charges.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Construction of a New MgB 2 Coating System for 1.3-GHz Superconducting RF Cavities at LANL

After many years of evaluating MgB 2 films prepared with various techniques for the application to superconducting radio-frequency (SRF) cavities, we have decided to build a system to coat full-size 1.3-GHz elliptical cavities. This paper describes the design and construction of the system. Additionally, we briefly describe experimental results with a small system and first tests with the new large system. In conclusion, we were able to obtain superconducting samples with a T c of up to 38 K with the small system, but we have not been able to get any superconducting samples with the new system yet.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Reduced Energetic Disorders in Dion–Jacobson Perovskites for Efficient and Spectral Stable Blue LEDs

Metal halide perovskites have witnessed great success in green, red, and near-infrared light-emitting diodes (LEDs), yet blue LEDs still lag behind. Reducing undesired energetic disorders – broad n -phases and halide segregation – is considered as the most critical strategy to further improve the performances. Here, the study reports a newly designed and synthesized di-ammonium ligand with rigid π -conjugated rings and additional methyl groups to construct Dion–Jacobson (DJ) structure. Augmented coordination from the extra ammonium site and increased effective bulkiness from methyl groups lead to better distribution control over conventional mono-ammonium ligands. This enhances the radiative recombination of blue emissions in the film with homogeneous energy landscape and improved surface morphology, as evidenced by a series of imaging and mapping techniques. As a result, it demonstrates DJ perovskite LEDs (PeLEDs) with peak external quantum efficiencies of ≈4% at 484 nm and ≈11% at 494 nm, which are among the top reported for pure DJ phase-based PeLEDs in the corresponding wavelength regions. The results deepen the understanding of regulating energetic disorders in perovskite materials via molecular engineering.

36 MATERIALS SCIENCE↗