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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Design and implementation of I/O performance prediction scheme on HPC systems through large-scale log analysis

Abstract Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units used by hundreds to thousands of users simultaneously. Applications from large numbers of users have diverse characteristics, such as varying computation, communication, memory, and I/O intensity. A good understanding of the performance characteristics of each user application is important for job scheduling and resource provisioning. Among these performance characteristics, I/O performance is becoming increasingly important as data sizes rapidly increase and large-scale applications, such as simulation and model training, are widely adopted. However, predicting I/O performance is difficult because I/O systems are shared among all users and involve many layers of software and hardware stack, including the application, network interconnect, operating system, file system, and storage devices. Furthermore, updates to these layers and changes in system management policy can significantly alter the I/O behavior of applications and the entire system. To improve the prediction of the I/O performance on HPC systems, we propose integrating information from several different system logs and developing a regression-based approach to predict the I/O performance. Our proposed scheme can dynamically select the most relevant features from the log entries using various feature selection algorithms and scoring functions, and can automatically select the regression algorithm with the best accuracy for the prediction task. The evaluation results show that our proposed scheme can predict the write performance with up to 90% prediction accuracy and the read performance with up to 99% prediction accuracy using the real logs from the Cori supercomputer system at NERSC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Draft Experimental Plan for Commercial SNF Degradation in Repository Environments with a Focus on Fracture Matrix Degradation

This report documents work performed supporting US Department of Energy (DOE) Nuclear Energy Spent Fuel and Waste Disposition, Spent Fuel and Waste Science and Technology, under work breakdown structure element 1.08.01.03.04, “Inventory and Waste Form Characteristics and Performance.” In particular, this report fulfills the M3 milestone, M3SF-21OR010309072 "Draft Experimental Plan for Commercial SNF Degradation in Repository Environments” as described in work package SF-21OR01030907 "SNF Degradation Testing-ORNL".This experimental plan is a collaboration between ORNL, SNL, ANL, and PNNL. It is intended to support source term model development and spent fuel degradation testing in a range of generic repository conditions. Potential testing and experiments to support validation of the Fuel Matrix Dissolution Model (FMDM) and the overall development/validation of repository source term modeling are discussed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

A Phenomenological Thermal Spray Wall Interaction Modeling Framework Applied to a High Temperature Ignition Assistant Device

Airborne compression ignition engines must operate with reliable ignition systems to achieve proper ignition at every cycle, particularly at high altitudes. Glow-plug-based ignition-assistant (IA) devices can provide the necessary energy to preheat the fuel and ensure ignitability of the fuel-air mixture. Ignitability of liquid sprays can be facilitated via direct impingement onto the hot IA surface, however this comes with adverse effects on the IA durability. Therefore, optimizing an IA’s design requires detailed understanding of the physics of fuel spray impingement of superheated surfaces. While spray impingement on relatively low wall temperatures has been extensively studied and appropriate numerical models have been proposed through the years, fundamental understanding of high-speed liquid spray impingement on superheated walls is still elusive. This work aims to formulate a phenomenological thermal spray-wall interaction framework for modeling the film-boiling-induced heat transfer, atomization, and dispersion of fuel spray droplets impinging onto a superheated IA device. A qualitative comparison of the new phenomenological model is performed against optical experiments from the literature of an F-24 fuel spray injected onto an IA device located 12 mm away from the injector tip. The temperature of the IA was set at 1400 K. The fuel injection pressure was 400 bar, while the ambient gas pressure and temperature were 30 bar and 800 K, respectively. The performance of the phenomenological model is evaluated in comparison with two other state-of-art models from the literature. A qualitative analysis of the different spray and fuel-air mixture characteristics is performed to outline the differences in the predictions offered by the new phenomenological model and the two state-of-art spray-wall interaction models.

droplet dispersion↗
DOE OSTI2024

End-Use Savings Shapes Measure Documentation: Dispatch Schedule Generation for Demand Flexibility Measures

This supplemental document describes the methodology used for determining the dispatch timing of various EUSS demand flexibility measures. Demand flexibility measures are designed to reduce/dispatch electricity demand in buildings during especially beneficial/critical times. The method used in this work utilizes predictions of building loads to generate a schedule that reflects the periods when the building's daily peak load occurs to support decision making in demand flexibility measures. The dispatch schedule generation method described in this document creates an hourly schedule that includes a load dispatch (peak) window for each day for a whole year based on load prediction, with options using different prediction methods: perfect prediction, bin-sampling method, fixed schedule, and outdoor air temperature (OAT)-based prediction method. The perfect prediction method performs a simulation to obtain the annual load profile as predicted load, representing the scenario of perfect load prediction. The bin-sampling method (1) categorizes days into representative bins by temperature characteristics, (2) performs simulations on sample days from each of those bins to create representative (or predicted) load, and (3) assigns representative loads for all days in a year based on the bin categorization. The fixed schedule method defines uniform start and end time of peak window with assumed fixed daily peak time, for all days in a season or a year. The OAT-based prediction method uses the statistics of OAT (minimum and maximum) as the indicators of peak load, with specified delay response time from building loads to temperature. Given the load prediction, daily peak periods are determined as a time window with specified length in each day that include the predicted daily peak load and with a secondary rule such as maximizing energy saving potential. The dispatch schedule generation method is not a standalone measure and is intended to be combined with other demand flexibility measures that could leverage the peak schedule and apply demand controls on specific systems or devices for demand response, such as measures described in "Measure Documentation - Thermostat Control for Load Shedding" and "Measure Documentation - Thermostat Control for Load Shifting".

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data

Abstract Background The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potential of machine learning models for understanding the connections between soil and biological phenotypes. We investigate an integrative framework performing accurate machine learning-based prediction of plant performance from biological, chemical, and physical properties of the soil via two models: random forest and Bayesian neural network. Results Prediction improves when we add environmental features, such as soil properties and microbial density, along with microbiome data. Different preprocessing strategies show that human decisions significantly impact predictive performance. We show that the naive total sum scaling normalization that is commonly used in microbiome research is one of the optimal strategies to maximize predictive power. Also, we find that accurately defined labels are more important than normalization, taxonomic level, or model characteristics. ML performance is limited when humans can’t classify samples accurately. Lastly, we provide domain scientists via a full model selection decision tree to identify the human choices that optimize model prediction power. Conclusions Our study highlights the importance of incorporating diverse environmental features and careful data preprocessing in enhancing the predictive power of machine learning models for soil and biological phenotype connections. This approach can significantly contribute to advancing agricultural practices and soil health management.

Aghdam, Rosa↗
DOE OSTI2024

Performances of a new generation tracking detector: the MEG II cylindrical drift chamber

Abstract The cylindrical drift chamber is the most innovative part of the MEG II detector, the upgraded version of the MEG experiment. The MEG II chamber differs from the MEG one because it is a single volume cylindrical structure, instead of a segmented one, chosen to improve its resolutions and efficiency in detecting low energy positrons from muon decays at rest. In this paper, we show the characteristics and performances of this fundamental part of the MEG II apparatus and we discuss the impact of its higher resolution and efficiency on the sensitivity of the MEG II experiment. Because of its innovative structure and high quality resolution and efficiency the MEG II cylindrical drift chamber will be a cornerstone in the development of an ideal tracking detector for future positron-electron collider machines.

Physics↗
DOE OSTI2023

SAS4A/SASSYS-1 Commercial Grade Dedication Example Report for a Generic Sodium Pool-Type Fast Reactor Application

In the U.S., a key component of the commercialization of advanced reactors is completion of a license application, which must ultimately be approved by the Nuclear Regulatory Commission (NRC). The approval of the license application by the NRC is contingent on satisfactory demonstration of the design basis and the response of the advanced reactor design to transient and accident scenarios using accepted codes and methods. This report describes the qualification and dedication requirements that the advanced reactor safety analysis system software SAS4A/SASSYS-1 are expected to need to fulfill to be used for sodium-cooled pool-type fast reactor licensing. The qualification and dedication requirements are identified through performance critical characteristics and evaluation model acceptance criteria representative of the advanced reactor design considered for licensing. This document captures, additionally, the verification process developed to demonstrate that the software fulfills the qualification and dedication requirements for a generic sodium-cooled pool-type fast reactor as part of the commercial grade dedication process. Like most software that has primarily existed in the research and development space, the most significant challenge facing SAS4A/SASSYS-1 for use in a licensing framework is the availability of a documentation basis describing the code pedigree. SAS4A/SASSYS-1 has been used for licensing of the fast flux test facility (FFTF) and the JOYO sodium-cooled fast reactor in Japan, as well as the design of the CRBR Plant. However, the historical verification and validation (V&V) activities supporting SAS4A/SASSYS-1 development do not align with modern software quality assurance (SQA) and V&V requirements. Two approaches to use of SAS4A/SASSYS-1 in a commercial licensing framework have been identified: commercial-grade dedication (CGD) and software qualification. The methods and requirements prescribed in the ASME NQA-1-2008/2009 Standard and Regulatory Guide 1.203 on the evaluation model development and assessment process (EMDAP) have been used as guidance to define the CGD and qualification processes, respectively. A qualification and dedication requirements matrix has been developed which utilizes fundamental software verification. In this process, software verification is defined as a software quality process aimed at defining software requirement specifications, developing software design documentation, and performing and documenting acceptance testing of the code against requirements. A key element of software qualification and dedication includes determination of software acceptance with respect to critical characteristics relevant to the functional requirements of the software. To assist with identification of cross-cutting transient phenomena and functional requirements, domestic SFR vendor designs have been reviewed to identify a reference SFR design. For this report, the reference design is defined as a pool-type reactor with metal alloy fuel, a liquid-metal intermediate heat transport system, and passive decay heat rejection systems. Given this reference, a series of high-level cross-cutting phenomena was identified for a general class of single-fault undercooling or reactivity insertion transients that scopes the design basis space, with the goal of assisting with prioritization of documentation development efforts for key transient models in SAS: 1) Reactivity feedback response prior to scram; 2) System-wide thermal inertia; 3) Transition in natural circulation flow regime in heat removal systems; 4) Decay heat generation; 5) Steady-state fuel characterization; 5) Clad/fuel behavior at elevated temperatures; 6) Point kinetics and decay heat; 7) Pump coastdown behavior; 8) Core flow redistribution in loss of forced convection; 9) Pool stratification. As a demonstration of CGD of SAS4A/SASSYS-1 for a sodium pool reactor, a software qualification and dedication gap analysis as it relates to code documentation has been performed. This effort leverages the framework established as part of the SAS4A/SASSYS-1 SQA Program. This CGD demonstration provides a framework that vendors can build upon to demonstrate the applicability of the SAS4A/SASSYS-1 software for licensing a sodium-cooled pool-type fast reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Characterization of dangling bond defects at the crystalline Si/SiO x interface in a polycrystalline Si passivating contact solar cell at room temperature with electrically detected magnetic resonance spectroscopy

Monocrystalline silicon solar cells can achieve photoconversion efficiencies exceeding 26%; however, performance-limiting defects that trap carriers continue to be a challenge. In this work, we have characterized Si solar cells with tunneling SiO x /polycrystalline-Si (poly-Si) passivating contacts (TOPCon) on As-doped Czochralski Si wafers with electrically detected magnetic resonance (EDMR) spectroscopy. We fabricated 2 × 20 mm 2 TOPCon-like mini solar cells with edge passivation alongside larger 4 cm 2 sister cells and obtained similar device characteristics. We performed EDMR spectroscopy at 300 K on two minicells with different degrees of surface passivation based on the recombination parameter, J o , values of 40 and 310 fA/cm2. We optimized the resolution and the signal-to-noise ratio of the EDMR response of the minicells by varying the forward bias voltage and the magnetic field modulation amplitude. We detect two distinct signals with EDMR spectroscopy, an axial-like signal at g = 2.009, 2.0087, and 2.0015, and an isotropic signal at g = 2.0024, which we attribute to Si dangling bonds (P b0 and P b centers) and boron–oxygen related defects, respectively, at or near the c-Si/SiO x interface. The EDMR signals were lower for the cell with a lower value of J o , while the ratio of the two defect populations was very similar. The EDMR signal increases with forward bias but drops to zero at bias voltages >0.5 V, consistent with interface defects within or near the boron-doped emitter depletion region. Our study demonstrates a method to fabricate minicells that can be characterized with EDMR spectroscopy to detect industrially relevant defects in TOPCon cells.

14 SOLAR ENERGY↗
DOE OSTI2020

Active Learning-driven Quantitative Synthesis-Structure-Property Relations for Improving Performance and Revealing Active Sites of Nitrogen-Doped Carbon for the Hydrogen Evolution Reaction

While quantitative structure-properties relations (QSPRs) have been developed successfully in multiple fields, catalyst synthesis affects structure and in turn performance, making simple QSPRs inadequate. Furthermore, catalysts often have multiple active sites preventing one from obtaining insights into structure-property relations. Here, we develop a data-driven quantitative synthesis-structure-property relation (QS2PRs) methodology to elucidate correlations between catalyst synthesis conditions, structural properties as well as observed performance and to provide fundamental insights into active sites and a systematic way to optimize practical catalysts. Here, we demonstrate the approach to the synthesis of nitrogen-doped catalysts (NDC) made via pyrolysis for the performance of the electrochemical hydrogen evolution reaction (HER), quantified by the onset potential and the current density. We determine crystallinity, nitrogen species type and fraction, surface area, and pore structure of the NDC’s using XRD, XPS, and BET characterization. We demonstrated that an active learning-based optimization combined with various elementary machine learning tools (regression, principal component analysis, partial least squares) can efficiently identify optimum pyrolysis conditions to tune structural characteristics and performance with concomitant savings in materials and experimental time. Unlike previous reports on the importance of pyridinic or graphitic nitrogen, we discover that the electrochemical performance is not driven by a single catalyst property; rather, it arises from a multivariate influence of nitrogen dopants, pore structure and disorder in the NDC materials. Identification of active sites can help mechanistic understanding and further catalyst improvement.

42 ENGINEERING↗
DOE OSTI2026

Highly Responsive Near-Infrared Photodetector Based on Contactless PdSe 2 Integration with a Few-Layered MoSe 2 Field-Effect Transistor

Two-dimensional (2D) semiconductors with narrow bandgaps are promising candidates for near- and far-infrared (IR) photodetection, particularly in the telecommunication spectral window. However, current low-bandgap IR photodetectors face significant challenges due to their high dark current, increased carrier recombination, and thermally generated noise. Here, in this work, a hybrid phototransistor is demonstrated by integrating direct, contact-free palladium diselenide (PdSe 2 ) as a highly responsive IR detection layer with a non-IR-absorbing molybdenum diselenide (MoSe 2 ) field-effect transistor (FET), using a near-IR source at a wavelength of λ = 1650 nm. Exfoliated PdSe 2 flakes integrated into a back-gated FET architecture exhibit ambipolar transport behavior, with extracted hole and electron mobilities of 24.8 cm 2 V –1 s –1 and 58.4 cm 2 V –1 s –1 , respectively. The devices show a clear photocurrent generation under the illumination of a λ = 1650 nm laser source, achieving a notable responsivity of ∼300 mA W -1 at an applied gate voltage of 15 V, which highlights the suitability of PdSe 2 as a narrow-bandgap material for photodetection. Photoresponsivity saturates and does not have any effect above an applied gate voltage of 15 V. To further tune the photoresponsivity performance continuously with the applied gate voltage, we construct a van der Waals heterostructure phototransistor, where few layers of PdSe 2 are directly transferred onto the 2D channel region of a MoSe 2 FET, while avoiding any contact with the metal electrodes. In this heterostructure, PdSe 2 works as the primary active IR-absorbing layer, while MoSe 2 provides high-performance FET characteristics. This spatial separation of absorption and transport facilitates efficient interlayer charge transfer and charge separation, resulting in high responsivities of up to 972 mA W –1 at near-IR wavelengths and a low power density of 1.5 mW/mm 2 . The responsivity of our photodetector is comparable to that of some state-of-the-art commercially available NIR photodetectors, highlighting the potential of PdSe 2 -based heterostructures as scalable, CMOS-compatible platforms for high-performance near-IR detection.

Infrared (IR) photodetectors↗
DOE OSTI2020

Performance Limits of an Alternating Current Electroluminescent Device

Abstract The use of an alternating current (AC) voltage is a simple, versatile method of producing electroluminescence from generic emissive materials without the need for contact engineering. Recently, it was shown that AC‐driven, capacitive electroluminescent devices with carbon nanotube network contacts can be used to generate and study electroluminescence from a variety of molecular materials emitting in the infrared‐to‐ultraviolet range. Here, performance trade‐offs in these devices are studied through comprehensive device simulations and illustrative experiments, enhancing understanding of the mechanism and capability of electroluminescent devices based on alternating as opposed to direct current (DC) schemes. AC‐driven electroluminescent devices can overcome several limitations of conventional DC‐driven electroluminescent devices, including the requirement for proper alignment of material energy levels and the need to process emitting materials into uniform thin films. By simultaneously optimizing device geometry, driving parameters, and material characteristics, the performance of these devices can be tuned. Importantly, the turn‐on voltage of AC‐driven electroluminescent devices approaches the bandgap of the emitting material as the gate oxide thickness is scaled, and internally efficient electroluminescence can be achieved using low‐mobility single‐layer emitter films with varying thicknesses and energy barrier heights relative to the contact.

Wang, Vivian↗
DOE OSTI2020

Characterization and identification of HPC applications at leadership computing facility

High Performance Computing (HPC) is an important method for scientific discovery via large-scale simulation, data analysis, or artificial intelligence. Leadership-class supercomputers are expensive, but essential to run large HPC applications. The Petascale era of supercomputers began in 2008, with the first machines achieving performance in excess of one petaflops, and with the advent of new supercomputers in 2021 (e.g., Aurora, Frontier), the Exascale era will soon begin. However, the high theoretical computing capability (i.e., peak FLOPS) of a machine is not the only meaningful target when designing a supercomputer, as the resources demand of applications varies. A deep understanding of the characterization of applications that run on a leadership supercomputer is one of the most important ways for planning its design, development and operation. In order to improve our understanding of HPC applications, user demands and resource usage characteristics, we perform correlative analysis of various logs for different subsystems of a leadership supercomputer. This analysis reveals surprising, sometimes counter-intuitive patterns, which, in some cases, conflicts with existing assumptions, and have important implications for future system designs as well as supercomputer operations. For example, our analysis shows that while the applications spend significant time on MPI, most applications spend very little time on file I/O. Combined analysis of hardware event logs and task failure logs show that the probability of a hardware FATAL event causing task failure is low. Combined analysis of control system logs and file I/O logs reveals that pure POSIX I/O is used more widely than higher level parallel I/O. Based on holistic insights of the application gained through combined and co-analysis of multiple logs from different perspectives and general intuition, we engineer features to "fingerprint" HPC applications. We use t-SNE (a machine learning technique for dimensionality reduction) to validate the explainability of our features and finally train machine learning models to identify HPC applications or group those with similar characteristic. To the best of our knowledge, this is the first work that combines logs on file I/O, computing, and inter-node communication for insightful analysis of HPC applications in production.

Liu, Zhengchun↗
DOE OSTI2023

Performance assessment of a real water source heat pump within a hardware-in-the-loop (HIL) testing environment

Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while also maintaining the thermal comfort of building occupants. As the pivotal point between building electricity consumption and indoor thermal comfort, high-efficiency electrical vapor-compression heat pumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on heat pump operation and performance when subjected to different weather conditions, building loads, and grid requests calls for investigation and verification via experimental testing with actual heat pumps integrated with real-time building and grid responses. This study introduces a Water-Source Heat Pump (WSHP) Hardware-in-The-Loop (HIL) Test Facility that is the first of its kind. This testbed utilizes a 2-ton variable speed water-to-air heat pump that is capable of interacting with a virtual environment currently comprised of an EnergyPlus (E+) building simulation, an agent-based occupant behavioral model, and a single U-tube ground-loop heat exchanger (GLHE) model. Detailed descriptions of the testbed’s physical design and operation, virtual environment, as well as their mutual communication is provided. An uncertainty analysis is also performed under manufacturer specified heating and cooling design conditions. This analysis shows that the total load across the WSHP’s demand side heat exchanger, i.e., the sum of its latent and sensible components, can be measured with a relative uncertainty of ± 10.4% and ± 3.6% in cooling and heating mode respectively. The WSHP’s coefficient of performance (COP) can be measured with relative uncertainties of ± 10.4% in cooling mode, and ± 3.7% in heating mode. A preliminary 24-h experimental demonstration is then performed utilizing the DOE prototype small commercial office building model in E+. The simulation takes place in Atlanta, GA on the date of 08/26/15 from 12:00 AM to 11:59 PM using TMY3 weather data. Here, the results from this demonstration show that over the course of this experiment the simulated outputs of zone dry-bulb temperature, zone humidity ratio, and WSHP inlet water temperature can be tracked by testbed emulators up to a root mean squared error (RMSE) of ± 0.27 °C, ± 0.376 g/kg, and ± 0.85 °C respectively. The WSHP’s dynamic behavioral characteristics and performance are also captured, and correspond well with the authors’ previous understanding of heat pump efficiency as a function of evaporator and condenser fluid inlet conditions respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Electrochemically-Formed Disordered Rock Salt ω-Li x V 9 Mo 6 O 40 as a Fast-Charging Li-Ion Electrode Material

Electrochemically-formed disordered rock salt compounds are an emerging class of Li-ion electrode materials for fast-charging energy storage. However, the specific factors that govern the formation process and the resulting charge storage performance are not well understood. Here, we characterize the transformation mechanism and charge storage properties of an electrochemically-formed disordered rock salt from V 9 Mo 6 O 40 (VMO). The crystal structure of VMO has similar motifs to that of α-V 2 O 5 , a well-studied analogue, but VMO has less mechanical flexibility due to additional corner-sharing octahedra in its structure. As a result, VMO undergoes a single-step transformation pathway, which we characterize through operando X-ray diffraction, and forms an unusual highly distorted lamellar microstructure, as we show with high-resolution transmission electron microscopy. The resulting Li x VMO material shows fast charging and other electrochemical characteristics and performance typical of many nanomaterials, even though the material is composed of relatively large particles.

25 ENERGY STORAGE↗
DOE OSTI2023

PDMS ‐silica composite gas separation membranes by direct ink writing

Abstract Polydimethylsiloxane (PDMS)‐based membranes containing amine‐functionalized and unfunctionalized silica particles were fabricated via direct ink writing for CO 2 /N 2 gas separation. The printability of the inks was evaluated by rheological measurements, while spectroscopy, microscopy, thermal measurements, and mechanical testing were employed to characterize the printed membranes. The surface morphology of the membranes revealed the absence of voids, demonstrating their suitability for gas separation. The printed membranes also exhibited desirable thermal and mechanical properties (i.e., thermal degradation temperature of 518 °C and tensile strength as high as 1.178 MPa with 529% elongation). The PDMS‐based membranes generally displayed high permeability for CO 2 but slightly low selectivity for the CO 2 /N 2 gas pair. The best‐combined permeability‐selectivity performance of 8794 barrer and selectivity of 11.64 was demonstrated by the printed PDMS membrane containing no SiO 2 fillers. The inclusion of unfunctionalized SiO 2 particles generally increased the membrane's gas permeability but compromised the selectivity. In contrast, membranes with amine‐functionalized silica showed improved selectivity compared to membranes containing unfunctionalized silica. Overall, the performance and characteristics offered by the PDMS/silica composite membranes demonstrated the potential of 3D printing as an economical and sustainable fabrication approach to developing materials for carbon capture applications.

Gutierrez, Dianne B.↗
DOE OSTI2021

Development and characteristics of ultra high-performance lightweight cementitious composites (UHP-LCCs)

Highlights: • An ultra high-performance lightweight cementitious composite (UHP-LCC) was designed. • The UHP-LCCs had ultra high strength (>120 MPa) and very low density (3 ). • The UHP-LCCs had high structural efficiency, good functional properties and superior durability. • The strategies and mechanisms on achieving UHP-LCCs with excellent performance were proposed. High strength and light weight are two recent opposite development trends of concrete. This study proposed a design concept of an ultra high-performance lightweight cementitious composite (UHP-LCC), which had a compressive strength of higher than 120 MPa and an air-dried density down to around 1800 kg/m{sup 3}. The UHP-LCCs were innovatively developed by incorporating micro-sized hollow particles with a high strength shell (hollow glass microspheres, HGM) into an ultra-high performance cementitious composite (UHPC). The roles of HGM in the UHP-LCCs were investigated by evaluating the reactivity of the HGM and the mechanisms on achieving the excellent mechanical properties, low density and superior durability were revealed. The Chapelle test results showed that the HGM exhibited some pozzolanic reactivity, which facilitated the reaction between the shell of HGM and the alkali hydration products of the paste matrix. This chemical reaction was conducive to improving the HGM-paste interface and enhancing the mechanical properties. With the use of microspheres with a high stiff shell, the fundamental properties of the UHP-LCCs including thermal insulation, sound absorption, resistance to water ingress and electrical resistivity were improved significantly. The strategies for preparing the UHP-LCCs with high structural efficiency and great performance were proposed. The results of this study provide a new approach for designing and producing a lightweight UHPC, which would be a promising material for long-span structures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Microstructural and micromechanical characteristics of ultra-high performance concrete with superabsorbent polymer (SAP)

In this study, the hydration product, C-S-H density, and pore structure at different layers from the drying surface were measured. Besides, the zone affected by the released internal curing water from SAP was identified by assessing the nanoindentation modulus. The results found that the SAP affected the moisture distribution and changed the evaporation and self-desiccation rates in the inner and outer layers. Such imposed moisture gradients affected the micromechanical properties of UHPC at different layers due to the change in the hydration degree of the binder, the density of C-S-H, and the pore structure of the matrix. The addition of SAP improved the hydration dynamics and transferred the LD C-S-H into HD or UHD C-S-H. As the distance from the drying surface increased, the affected zone of SAP increased from 60 to 120 μm, showing the more effectiveness of SAP at inner layers.

36 MATERIALS SCIENCE↗