Rapid Fatigue Characterization via Infrared Thermography of AM-CM Composites
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Manoharan, Nithinkumar↗
Engineering topics
Kumar, Vipin
Publications and source records attributed to Kumar, Vipin.
A scalable framework for quantifying field-level agricultural carbon outcomes
Agriculture contributes nearly a quarter of global greenhouse gas (GHG) emissions, which is motivating interest in adopting certain farming practices that have the potential to reduce GHG emissions or sequester carbon in soil. The related GHG emission (including N 2 O and CH 4 ) and changes in soil carbon stock are defined here as “agricultural carbon outcomes”. Accurate quantification of agricultural carbon outcomes is the basis for achieving emission reductions for agriculture, but existing approaches for measuring carbon outcomes (including direct measurements, emission factors, and process-based modeling) fall short of achieving the required accuracy and scalability necessary to support credible, verifiable, and cost-effective measurement and improvement of these carbon outcomes. Here we propose a foundational and scalable framework to quantify field-level carbon outcomes for farmland, which is based on the holistic carbon balance of the agroecosystem: Agroecosystem Carbon Outcomes = Environment (E) × Management (M) × Crop (C). Following a comprehensive review of the scientific challenges associated with existing approaches, as well as their tradeoffs between cost and accuracy, we propose that the most viable path for the quantification of field-level carbon outcomes in agricultural land is through an effective integration of various approaches (e.g. diverse observations, sensor/in-situ data, and modeling), defined as the “System-of-Systems” solution. Such a “System-of-Systems” solution should simultaneously comprise the following components: (1) scalable collection of ground truth data and cross-scale sensing of environment variables (E), management practices (M), and crop conditions (C) at the local field level; (2) advanced modeling with necessary processes to support the quantification of carbon outcomes; (3) systematic Model-Data Fusion (MDF), i.e. robust and efficient methods to integrate sensing data and models at each local farmland level; (4) high computation efficiency and artificial intelligence (AI) to scale to millions of individual fields with low cost; and (5) robust and multi-tier validation systems and infrastructures to ensure solution fidelity and true scalability, i.e. the ability of a solution to perform robustly with accepted accuracy on all targeted fields. In this regard, we provide here the detailed scientific rationale, current progress, and future research and development (R&D) priorities to achieve different components of the “System-of-Systems” solution, thus accomplishing the Environment×Management×Crop framework to quantify field-level agricultural carbon outcomes.
54 ENVIRONMENTAL SCIENCES↗
Bioinspired design toward nanocellulose-based materials
Nature provides lots of inspiration for material and structural design for various applications. Deriving design principles from the investigation of nature can provide a rich source of inspiration for the development of multifunctional materials. The bioinspired design templates mainly include mussels, nacre, and various plant species. As a sustainable and renewable feedstock, nanocellulose can be used to fabricate advanced materials with multifunctional properties through bioinspired designs. However, challenges and opportunities remain for realizing the full potential in the design of novel materials. Here, this article reviewed recent development in the bioinspired nanocellulose based materials and their application. This article summarizes the functions (e.g., surface wetting) and applications (e.g., composite) of bioinspired nanocellulose-based materials. The bioinspired design templates are discussed along with strategies, advantages, and challenges to the development of synthetic mimics. Additionally, mechanisms and processes (e.g., chemical modification, self-assembly) leading to biomimetic design are discussed. Finally, future research directions and opportunities of bioinspired nanocellulose-based materials are highlighted.
36 MATERIALS SCIENCE↗
The Influence of Carbon Fiber Composite Specimen Design Parameters on Artificial Lightning Strike Current Dissipation and Material Thermal Damage
Previous artificial lightning strike direct effect research has examined a broad range of specimen design parameters. No works have studied how such specimen design parameters and electrical boundary conditions impact the dissipation of electric current flow through individual plies. This article assesses the influence of carbon fiber composite specimen design parameters (design parameters = specimen size, shape, and stacking sequence) and electrical boundary conditions on the dissipation of current and the spread of damage resulting from Joule heating. Thermal-electric finite element (FE) modelling is used and laboratory scale (<1 m long) and aircraft scale (>1 m long) models are generated in which laminated ply current dissipation is predicted, considering a fixed artificial lightning current waveform. The simulation results establish a positive correlation between the current exiting the specimen from a given ply and the amount of thermal damage in that ply. The results also establish that the distance to ground, from the strike location to the zero potential boundary conditions (ground), is the controlling factor which dictates the electric current dissipation in each ply. Significantly, this distance to ground is dependent on each of the specimen shape, dimensions, stacking sequence, and location of ground boundary conditions. Therefore, it is not possible to decouple current dissipation and damage from specimen design and boundary condition setup. However, it is possible to define a specimen size for a given specimen shape, stacking sequence, and waveform which limit the influence of specimen dimensions on the resulting current distribution and damage. For a rectangular specimen design which appears in literature multiple times, as 100 × 150 mm and with a stacking sequence of [45/0/-45/90] 4s , a specimen design of greater than 300 × 200 mm is required to limit the influence of specimen dimensions on current distribution and damage.
36 MATERIALS SCIENCE↗
A novel additive manufacturing compression overmolding process for hybrid metal polymer composite structures
Metal polymer composites combining low density, high strength composites with highly ductile and tough metals have gained traction over the last few decades as lightweight and high-performance materials for industrial applications. However, the mechanical properties are limited by the interfacial bonding strength between metals and polymers achieved through adhesives, welding, and surface treatment processes. In this paper, a novel manufacturing process combining additive manufacturing and compression molding to obtain hybrid metal polymer composites with enhanced mechanical properties is presented. Additive manufacturing enabled deposition of polymeric material with fibers in a predetermined pattern to form tailored charge or preform for compression molding. Here, a grade 300 maraging steel triangular lattice is first fabricated using AddUp FormUp350 laser powder bed system and compression overmolded with additively manufactured long carbon fiber-reinforced polyamide-6,6 (40% wt. CF/PA66) preform. The fabricated hybrid metal polymer composites showed high stiffness and tensile strength. The stiffness and failure characteristics determined from the uniaxial tensile tests were correlated to a finite element model within 20% deviation. Fractographic analyses was performed using microscopy to investigate failure mechanisms of the hybrid structures.
36 MATERIALS SCIENCE↗
Enhanced through-thickness electrical conductivity and lightning strike damage response of interleaved vertically aligned short carbon fiber composites
Through-thickness electrical conductivity of carbon fiber reinforced polymers (CFRPs) is a key characteristic that determines the severity of lighting strike-induced damage. Carbon Fibers (CFs) are inherently electrically conductive and therefore provide high conductivity in the direction of the fiber orientation. However, electrical conductivities through the thickness and orthogonal to the CF orientation in CFRPs are governed by the insulating polymer matrix present between CFs. Here, in this work, through the thickness alignment of short CFs in between layers of CFRP laminates is demonstrated to improve the through-thickness electrical conductivity. Composites with interleaved vertically aligned short CF fibers (<150 μm) will be referred as V-fiber composites hereafter. The effect of the V-fiber on the lightning strike damage is evaluated against an artificial lightning strike of 100 kA (modified waveform A of SAE ARP-5412B standard). The improved through-thickness electrical conductivity of CFRP laminates (1.15 S/cm) through vertical alignment of short CFs was compared to reference CFRP laminates (0.13 S/cm) and was found to dissipate the artificial lightning strike current more efficiently. The surface damage after the artificial lightning strike in the V-fiber composites was reduced to 12.69 cm 2 compared to the reference CFRP surface damage of 57.67 cm 2 , a 78% reduction. It was also demonstrated that Joule heat generated due to lightning strike on the composites was significantly less than the reference sample using infrared (IR) thermography. A high retention (up to 78%) of flexural properties (modulus and strength) was observed in V-fiber composites post lightning strike impact as compared to only 47% retention in the reference panel.
42 ENGINEERING↗
Carbon Nanotube and Graphene Oxide Reinforced Composites for Lightning Strike Protection of Composite Structures
Carbon fiber reinforced plastics (CFRP) composites have become the primary materials in the aerospace industry. Future transportation means, such as urban air mobility (UAM), will be employing CFRP structures. However, lightning strike damage on composite structures is a serious concern. CFRP composites possess low through-thickness electrical conductivity (≈ 1 S/m), which can cause extreme resistive heat in the event of lightning strikes. Research on polymeric lightning strike protection has gained momentum in the past few years. Researchers have studied various conductive fillers to improve the CFRP performance against lightning strikes. Carbon nanotubes (CNTs) and graphene oxide (GO) have been studied as future lightning Strike Protection (LSP) materials the most. The use of CNT and GO-based composites has shown improved mechanical properties and improved electrical conductivity of the composites. Researchers investigated CNTs and GO as the fillers to the matrix system, sizing the carbon fibers and the surface coating on top of the CFRP surface. This chapter highlights the remarkable improvement in the lightning damage suppression of CNT and GO-based composites and their structural applications. Special attention is given to their potential use as LSP material in future aircraft.
Kumar, Vipin↗
Effects of Mechanical Recycling on Carbon Fiber-Based Hybrid Composites
Carbon fiber (CF) reinforced composites are high-performing, highly utilized material systems historically used in aerospace. As the cost of CF decreases, other industries, such as automotive and energy generation, seek to adopt CF composites into their applications. A sudden increase in CF demand may create supply chain issues if the adoption happens without scaling up of the CF production. A solution for reducing the reliance on CF is to substitute some portion of the CF content with another fiber type without significantly reducing the material properties. When multiple reinforcing fillers are introduced into a composite system, the materials system is often referred to as a hybrid composite and in this case a CF-based hybrid composite. To further relieve reliance on CF and with sustainable manufacturing becoming more prominent in industry, mechanical recycling can be employed to replace all or a percentage of the virgin material content. Utilizing recycled content in place of virgin content will further aid in reducing the reliance on virgin CF and decrease overall material costs. Here, the effects of utilizing mechanically recycled feedstocks on the mechanical properties of injection molded samples are explored to understand the feasibility of re-manufacturing recycled CF-based hybrid composites. By determining the mechanical properties and mechanisms in which the properties change through varying recycled content, the assessment of how the material will perform in other manufacturing processes can be inferred. As a result, industry will gain better insight into utilizing mechanically recycled feedstocks to reduce their reliance on the CF supply chain.
36 MATERIALS SCIENCE↗
EFFECTS OF MECHANICAL RECYCLING ON CARBON FIBER-BASED HYBRID COMPOSITES
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Rencheck, Mitch↗
LARGE SCALE POLYMER ADDITIVE MANUFACTURING OF LIGHTWEIGHT FOAM STRUCTURES
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Kunc, Vlastimil↗
Printed Strain Gauges for Anthropomorphic Test Dummies for Vehicle Crash Testing
In Phase 1 of the technical collaboration between Oak Ridge National Laboratory (ORNL) and Humanetics, additive manufacturing was studied as a method to produce high strain – strain gauges that are embedded in an additively manufactured (AM) anthropomorphic crash test dummy (ATD) to provide high fidelity data to significantly improve vehicle safety. In this study commercially available conductive filament was acquired and the mechanical properties were tested for use in this application. The design space of embedded printed strain gauges was explored with multiple configurations printed and tested for performance. The testing resulted in finding that commercially available filament materials were unable to meet the performance requirements. Finally, an extensive literature survey was performed on advanced manufacturing techniques and novel high strain conductive materials to manufacture strain gauges that can be embedded in to the AM ATD. Humanetics have taken the literature survey and have reached out to material suppliers such as Techmer to provide custom blends of materials for testing. Humanetics will continue to build off of the research that was performed and test custom materials for use in AM ATDs.
36 MATERIALS SCIENCE↗
MODELLING FIBER ORIENTATION DURING ADDITIVE MANUFACTURING COMPRESSION MOLDING PROCESSES
The production of high-performance thermoplastic composites reinforced with short carbon fibers can be achieved by a novel “additive manufacturing-compression molding” technique. An advantage of such combination is two-fold: controlled fiber orientation in additive manufacturing and less void content by compression molding. In this study, a computational fluid dynamics model has been developed to predict the behavior of printed layers during fiber-reinforced thermoplastic extrusion and subsequent compression molding. The fiber orientation was modelled with a simple quadratic closure model. The interaction between the fibers is included using a rotary diffusion coefficient which becomes significant in concentrated regimes. Finally, the second order orientation tensor is coupled with the momentum equation as an anisotropic part of the stress term. The effect of processing parameters on the behavior of printed layers was investigated to determine the favorable printing scenarios. The developed numerical model enables design of high-performance composites with tunable mechanical properties.
Seta, Berin↗
MODELLING OF ADDITIVE MANUFACTURING – COMPRESSION MOLDING PROCESS USING COMPUTATIONAL FLUID DYNAMICS
A computational fluid dynamics model has been developed to predict the behavior of a printed strands during a novel material extrusion additive manufacturing and compression molding process. While the traditional additive manufacturing process enables control over the fiber orientation within the part, it would also result in high void content. On the other hand, compression molding produces parts with low porosity levels at rapid processing cycle time but lacks control over the microstructure. The novel additive manufacturing – compression molding (AM-CM) integrating both these processes offers control over both the microstructure and porosity to manufacturing high performance composite parts. The numerical model developed here enables to analyze the effect of processing parameters on the behaviour of printed layer that is subsequently compressed and to determine the optimal printing parameters for high-performance composite part design.
Seta, Berin↗
Theory-guided experimental design in battery materials research
A reliable energy storage ecosystem is imperative for a renewable energy future, and continued research is needed to develop promising rechargeable battery chemistries. To this end, better theoretical and experimental understanding of electrochemical mechanisms and structure-property relationships will allow us to accelerate the development of safer batteries with higher energy densities and longer lifetimes. This Review discusses the interplay between theory and experiment in battery materials research, enabling us to not only uncover hitherto unknown mechanisms but also rationally design more promising electrode and electrolyte materials. We examine specific case studies of theory-guided experimental design in lithium-ion, lithium-metal, sodium-metal, and all-solid-state batteries. We also offer insights into how this framework can be extended to multivalent batteries. To close the loop, we outline recent efforts in coupling machine learning with high-throughput computations and experiments. Last, recommendations for effective collaboration between theorists and experimentalists are provided.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Anisotropic thermal behavior of extrusion-based large scale additively manufactured carbon-fiber reinforced thermoplastic structures
Large format additive manufacturing (AM) enables rapid manufacturing of large parts and structures with minimum waste in material and energy. Extrusion-based AM deposition processes provide parts with highly anisotropic thermal properties, which are not typically reflected in textbook values for these materials. In order to develop accurate models that describe the directionally dependent thermal behavior of these materials in processing and service, accurate measurements of specific heat capacity and thermal conductivity are required. Here, this work characterizes, documents, and analyzes the effect of the anisotropic nature of the extrusion-based deposition process on the specific heat capacity and thermal conductivity of the resulting AM products. All measurements were made over a temperature range of 20–180°C using the transient plane source technique, also referred to as the hot disk technique. Three of the most commonly used large format AM feedstock materials that utilize carbon fiber reinforcement were examined in this work: acrylonitrile butadiene styrene, polyphenylene sulfide and polyphenylsulfone. Finally, these findings can serve as a thermal design/process guideline for future large format AM applications.
36 MATERIALS SCIENCE↗
Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?
Abstract The global decline of water quality in rivers and streams has resulted in a pressing need to design new watershed management strategies. Water quality can be affected by multiple stressors including population growth, land use change, global warming, and extreme events, with repercussions on human and ecosystem health. A scientific understanding of factors affecting riverine water quality and predictions at local to regional scales, and at sub‐daily to decadal timescales are needed for optimal management of watersheds and river basins. Here, we discuss how machine learning (ML) can enable development of more accurate, computationally tractable, and scalable models for analysis and predictions of river water quality. We review relevant state‐of‐the art applications of ML for water quality models and discuss opportunities to improve the use of ML with emerging computational and mathematical methods for model selection, hyperparameter optimization, incorporating process knowledge into ML models, improving explainablity, uncertainty quantification, and model‐data integration. We then present considerations for using ML to address water quality problems given their scale and complexity, available data and computational resources, and stakeholder needs. When combined with decades of process understanding, interdisciplinary advances in knowledge‐guided ML, information theory, data integration, and analytics can help address fundamental science questions and enable decision‐relevant predictions of riverine water quality.
54 ENVIRONMENTAL SCIENCES↗
Hydrogen bond–induced aqueous-phase surface modification of nanocellulose and its mechanically strong composites
Aqueous-phase surface modification of nanocellulose is desirable because nanocellulose is generally produced via water-based fibrillation. In this study, a hydrogen bond–induced surface modification of cellulose nanofibrils (CNFs) in water was developed. Tannic acid and polyvinylpyrrolidone were chosen to modify the CNFs because of their strong capacity for hydrogen bond formation. By tuning the hydrogen bond formation between CNFs, tannic acid, and polyvinylpyrrolidone, CNFs with different surface hydrophilicity were achieved. Additionally, the modified CNFs can assemble into strong and tough composites owing to the hydrogen bond network in the system. Modified CNFs demonstrated 76% higher tensile strength and 100% higher toughness than those of unmodified CNFs, reaching 162 MPa and 12.7 MJ/m 3 , respectively. This study provides a new water-based modification strategy for the nanocellulose, leading the way toward producing strong nanocellulose composites via noncovalent interaction.
36 MATERIALS SCIENCE↗
Joining technique for in-oven/autoclave molds manufactured by large scale polymer additive manufacturing
Large scale additive manufacturing (AM) of fiber-reinforced polymer composites has gained traction in the mold and die community over the last decade, largely due to reduced material cost and lead time. However, limitations in mold size remain present due to printer volume constraints and costs associated with large format machines. Here, this paper describes a method for producing additively manufactured polymer molds in segments with an O-ring joint design, which can be machined and subsequently assembled for autoclave applications. The developed joining mechanism allows for maintaining the vacuum integrity during the cure cycle while accounting for the anisotropic nature of the additively manufactured polymer molds. Over a range of tested temperatures, 20–200 °C, the multi-part mold joining design was able to achieve full vacuum of ∼73.7 cmHg (29 inchHg) and maintain a vacuum integrity with vacuum losses less than 1.5 cmHg/5min (0.6 inchHg).
Joining↗