Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “improved engine efficiency”

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 253 records · Page 14

Lean-Stratified Combustion System with Miller Cycle for Downsized Boosted Application - Part I

Automotive manufacturers relentlessly explore engine technology combinations to achieve reduced fuel consumption under continued regulatory, societal and economic pressures. For example, technologies enabling advanced combustion modes, increased expansion to effective compression ratio, and reduced parasitics continue to be developed and integrated within conventional and hybrid propulsion strategies across the industry. A high-efficiency gasoline engine capable for use in conventional or hybrid electric vehicle platforms is highly desirable. This paper is the first to two papers describing the development of a combustion system combining lean-stratified combustion with Miller cycle for downsized boosted applications. The work was completed under a multi-year US DOE project. The goal was to define a light-duty engine package capable of achieving a 35% fuel economy improvement at US Tier 3 emission standards over a naturally aspirated stoichiometric baseline vehicle. A multi-mode combustion system was developed enabling highly efficient lean-stratified operation at light-load and stoichiometric Miller-cycle operation at mid- to highloads. Some of the unique challenges in synergistically combining the two concepts are highlighted in this paper. Here, a central direct-injection four-valve layout was designed with high-tumble ports and a bowl-in-piston capable of stable operation under highly dilute (lean plus EGR) mixtures when properly matched to fuel spray characteristics, a multiple-injection strategy, and a high-energy ignition system. Other challenges specific to meeting exhaust emissions requirements with a high-efficiency engine are also explored in this study. In this Part 1 of the paper, the single-cylinder combustion system design, analysis, and testing is described. Multicylinder engine system design, analysis and development is described in Part 2 of the paper.

33 ADVANCED PROPULSION SYSTEMS↗

Efficient Training of Deep Neural Operator Networks via Randomized Sampling

Neural operators (NOs) employ deep neural networks to learn the mappings between infinitedimensional function spaces. Deep operator network (DeepONet), a popular NO architecture, has demonstrated success in the real-time prediction of complex dynamics across various scientific and engineering applications. In this work, we introduce a random sampling technique to be adopted during the training of DeepONet, aimed at improving the generalization ability of the model, while significantly reducing the computational time. The proposed approach targets the trunk network of the DeepONet model that outputs the basis functions corresponding to the spatiotemporal locations of the bounded domain on which the physical system is defined. While constructing the loss function, DeepONet training traditionally considers a uniform grid of spatiotemporal points at which all the output functions are evaluated for each iteration. This approach leads to a larger batch size, resulting in poor generalization and increased memory demands, due to the limitations of the stochastic gradient descent (SGD) optimizer. The proposed random sampling over the inputs of the trunk net mitigates these challenges, improving generalization and reducing the memory requirements during training, resulting in significant computational gains. We validate our hypothesis through three benchmark examples, demonstrating substantial reductions in training time while achieving comparable or lower overall test errors relative to the traditional training approach. Our results indicate that incorporating randomization in the trunk network inputs during training enhances the efficiency and robustness of DeepONet, offering a promising avenue for improving the framework’s performance in modeling complex physical systems.

Karumuri, Sharmila [Department of Civil & Systems ↗

BETO 2021 Peer Review - Improving Formate Upgrading by Cupriavidus Necator 2.3.2.111

Formate can be generated by electrocatalytic reduction of CO2 and has been proposed as a soluble intermediate for the storage of carbon and energy. Biological systems capable of assimilating formate could enable conversion of formate generated from low-cost renewable energy and waste CO2 to myriad fuels and chemicals. To that end, the goal of this project is to develop the natural formatotroph Cupriavidus necator as a robust microbial chassis for efficient conversion of formate to value-added products. Using a combination of laboratory evolution and rational engineering, we have identified mutations and genetic deletions that improve its growth rate and biomass yield on formate by 1.2X. Using RNA-seq transcriptomics, we are elucidating the mechanisms that underly these improvements and anticipate this will contribute to our understanding of formate conversion. We have also engineered C. necator to convert formate to the potential polymer precursor 2-hydroxymuconate semialdehyde (2HMS) by introducing an exogenous pathway and deleting competing pathways and demonstrated production and robust growth using a pH-stat bioreactor. Final techno-economic analysis and life-cycle assessment on biological production of 2HMS from formate will enable the DOE and other stake holders to evaluate the economic and environmental impact of this project and related technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Piston Bowl Geometry Effects on Gasoline Compression Ignition in a Heavy-Duty Diesel Engine

A design optimization campaign was conducted to search for improved combustion profiles that enhance gasoline compression ignition in a heavy-duty diesel engine with a geometric compression ratio of 17.3. A large-scale design of experiments approach was used for the optimization, employing three-dimensional computational fluid dynamics simulations. The main parameters explored include geometric features, injector specifications, and swirl motion. Both stepped-lip and re-entrant bowls were included in order to assess their respective performance implications. A total of 256 design candidates were prepared using the software package CAESES for automated and simultaneous geometry generation and combustion recipe perturbation. The design optimization was conducted for three engine loads representing light to medium load conditions. The design candidates were evaluated for fuel efficiency, emissions, fuel-air mixing, and global combustion behavior. Simulation results showed that the optimum designs were all stepped-lip bowls, due to improvements in fuel-air mixing, as well as reduced heat loss and emissions formation. Improvements in indicated specific fuel consumption of up to 3.2% were achieved while meeting engine-out NOx emission targets of 1-1.5 g/kW center dot h. Re-entrant bowls performed worse compared to the baseline design, and significant performance variations occurred across the load points. Specifically, the re-entrant bowls were on par with the stepped-lip bowls under light load conditions, but significant deteriorations occurred under higher load conditions. As a final task, selected optimized designs were then evaluated under full-load conditions.

CFD↗

Zinc batteries for grid-scale energy storage: Challenges, opportunities, and future directions

The global electricity sector is undergoing rapid transformation, increasing demand for reliable stationary energy storage and intensifying the need for safe, cost-effective, and scalable technologies for grid-scale applications. While lithium-ion batteries currently dominate the market, concerns over cost, safety, and resource availability motivate the exploration of alternative chemistries. Zinc-based batteries have emerged as a promising option due to the abundance, low cost, and wide geographic distribution of zinc, combined with the inherent safety of aqueous electrolytes. This perspective examines the potential of zinc batteries for stationary energy storage, with particular focus on rechargeable zinc-air systems. We discuss the evolution of zinc battery technologies and compare zinc-air, zinc-bromine, nickel-zinc, and aqueous zinc-ion chemistries, highlighting their advantages for grid applications. Key challenges limiting rechargeable zinc battery performance are analyzed, including dendrite formation and corrosion at the zinc anode, electrolyte degradation from carbonation and evaporation, and sluggish oxygen electrocatalysis at the air cathode. Emerging strategies to address these limitations are reviewed, including advanced electrode architectures, electrolyte engineering, catalyst development, and system-level design improvements. Lastly, we outline future research directions and opportunities for developing durable, efficient, and economically viable zinc-based energy storage systems for grid-scale applications.

Aqueous electrolytes↗

Less can be more: Insights on the role of electrode microstructure in redox flow batteries from two-dimensional direct numerical simulations

Understanding how to structure a porous electrode to facilitate fluid, mass, and charge transport is key to enhancing the performance of electrochemical devices, such as fuel cells, electrolyzers, and redox flow batteries (RFBs). Here, using a parallel computational framework, direct numerical simulations are carried out on idealized porous electrode microstructures for RFBs. Strategies to improve an electrode design starting from a regular lattice are explored. By introducing vacancies in the ordered arrangement, it is possible to achieve higher voltage efficiency at a given current density, thanks to improved mixing of reactive species, despite reducing the total reactive surface. Careful engineering of the location of vacancies, resulting in a density gradient, outperforms disordered configurations. Our simulation framework is a new tool to explore transport phenomena in RFBs, and our findings suggest new ways to design performant electrodes.

25 ENERGY STORAGE↗

Thermally robust and highly stable method for splicing silica glass fiber to crystalline sapphire fiber

This research reports an advancement in splicing silica glass fiber to sapphire single-crystal optical fiber (SCF) using a specialized glass processing device, including data that demonstrate the thermal stability of the splice to 1000°C. A filament heating process was used to produce a robust splice between the dissimilar fibers. A femtosecond laser is used to inscribe a fiber Bragg gratings sensor into the SCF to measure the high-temperature capabilities and signal attenuation characteristics of the splice joint. The experimental results demonstrate that the proposed splicing method produces a splice joint that is robust, stable, repeatable, and withstands temperatures up to 1000°C with a low attenuation of 0.5 dB. Here, the proposed method allows placement of SCF-based sensors in the extreme environments encountered in various engineering fields, such as nuclear, chemical, aviation, and metals manufacturing, to enable improvements in process monitoring, product quality, and production efficiency.

36 MATERIALS SCIENCE↗

Metalorganic chemical vapor deposition of ZnGeN 2 films on GaN: effects of cation stoichiometry on surface morphology and crystallinity

Novel optoelectronic device designs based on the heterostructures of III-N and II-IV-N 2 are promising to advance device performance significantly. For example, by utilizing InGaN-ZnGeN 2 quantum well (QW) structures instead of pure InGaN, the band structure engineering in the QW active region can lead to improved electron-hole wavefunction overlap, and thus enhance the radiative efficiency for photon generation. These novel heterostructures have great potential to address the current challenge of low quantum efficiency in InGaN QW based light emitting diodes emitting in green and beyond. The materials development of ZnGeN 2 is still at an early stage as compared to the much matured GaN material system. In an ideal octet rule preserving ordered structure of ZnGeN 2 , every N atom is coordinated by exactly two Zn and two Ge atoms. However, local violation of octet rule can be caused by non-ideal coordination of N by the cations. The disordered structure is thermodynamically less favorable but can still be achieved, for example, in kinetics-limited growth regime. The ordered ZnGeN 2 has a bandgap very close to that of GaN (~3.4 eV) and a lattice mismatch of <0.1% with GaN. Interestingly, the valence band of ZnGeN 2 has been predicted to be ~1 eV above that of GaN, which has inspired novel designs for high efficiency light emitters. In this work, we investigated the metalorganic chemical vapor deposition (MOCVD) of ZnGeN 2 films on GaN/c-sapphire templates. Diethylzinc (DEZn), germane (GeH4) and ammonia were used as the precursors for Zn, Ge and N, respectively. A systematic study was conducted to investigate the cation stoichiometry as a function of growth temperature (TG), total reactor pressure (P) and DEZn/GeH 4 molar flow rate ratio (RII/IV). Under the investigated growth window, the Zn/(Zn+Ge) composition in the films, determined from energy dispersive X-ray spectroscopy, decreased monotonically with increase in TG but increased with increase in P and RII/IV. Atom probe tomography data did not indicate the presence of any secondary phases such as Zn 3 N 2 or Ge 3 N 4 . The surface morphology and crystallinity of the grown films had strong correlation with the Zn/(Zn+Ge) composition. The scanning electron microscopy images showed that the near-stoichiometric films have planar surfaces whereas Zn-rich films had crystallites on their surface and the Zn-poor films had faceted surface. Scanning transmission electron microscopy (STEM) imaging revealed that the Zn-rich and Zn-poor films have columnar and filament-like morphology, respectively, whereas the near-stoichiometric films have continuous film-like cross-sectional morphology. TEM nano-diffraction patterns as well as X-ray diffraction 2θ-ω scan profiles indicate that the near stoichiometric films are single crystalline. Nano-diffraction pattern of the stoichiometric films resembled that of a disordered ZnGeN 2 structure. Room temperature Raman spectra of near-stoichiometric films showed only the phonon density of states like features of a cation disordered ZnGeN 2 . Cathodoluminescence and photoluminescence spectra measured at different temperatures had similar features with peak emission wavelength at ~ 2 eV. In conclusion, the stoichiometry of ZnGeN 2 films can be widely tuned by tuning the MOCVD growth parameters. The surface morphology and the crystallinity of the films were found to have strong correlation with the Zn/(Zn+Ge) composition. The stoichiometric ZnGeN 2 films grown on GaN were demonstrated with uniform surface morphology and high crystalline quality. The results from this work will provide pathway to implement ZnGeN 2 in device structures.

Karim, Md Rezaul↗

A New Modeling Framework for Geothermal Operational Optimization with Machine Learning (GOOML)

Geothermal power plants are excellent resources for providing low carbon electricity generation with high reliability. However, many geothermal power plants could realize significant improvements in operational efficiency from the application of improved modeling software. Increased integration of digital twins into geothermal operations will not only enable engineers to better understand the complex interplay of components in larger systems but will also enable enhanced exploration of the operational space with the recent advances in artificial intelligence (AI) and machine learning (ML) tools. Such innovations in geothermal operational analysis have been deterred by several challenges, most notably, the challenge in applying idealized thermodynamic models to imperfect as-built systems with constant degradation of nominal performance. This paper presents GOOML: a new framework for Geothermal Operational Optimization with Machine Learning. By taking a hybrid data-driven thermodynamics approach, GOOML is able to accurately model the real-world performance characteristics of as-built geothermal systems. Further, GOOML can be readily integrated into the larger AI and ML ecosystem for true state-of-the-art optimization. This modeling framework has already been applied to several geothermal power plants and has provided reasonably accurate results in all cases. Therefore, we expect that the GOOML framework can be applied to any geothermal power plant around the world.

15 GEOTHERMAL ENERGY↗

Impact of Biofuel Blending on Hydrocarbon Speciation and Particulate Matter from a Medium-Duty Multimode Combustion Strategy

The U.S. Department of Energy’s Co-Optima initiative simultaneous focused on diversifying fuel sources, improving efficiency, and reducing emissions through using novel combustion strategies and sustainable fuel blends. For medium-duty/heavy-duty diesel engines, research in this area has led to the development of a multimode strategy that uses premixed charge compression ignition (PCCI) at low loads and conventional diesel combustion (CDC) at mid–high loads. The aim of this study was to understand how emissions were impacted when using PCCI instead of CDC at low loads and switching to an oxygenated biofuel blend. It provides a detailed speciation of the hydrocarbon (HC) and particulate matter (PM) emissions from a multimode medium-duty engine operating at low loads in PCCI and CDC modes and high loads in CDC. The effect of the oxygenated biofuel blend on emissions was studied at all three mode–load conditions using #2 ULSD and a bio-derived fuel (25% hexyl hexanoate (HHN)) blended in #2 ULSD. The PCCI mode effectively decreased NOx, total HC, and PM/PN emissions, with a substantial decrease in larger particles (≥50 nm). A PM/PN reduction was observed at high loads with the 25% HHN fuel. While the total HC emissions were not impacted by fuel type, the detailed HC analysis exposed changes in the HC’s composition.

09 BIOMASS FUELS↗

Over 11% Efficient Eco-Friendly Kesterite Solar Cell: Effects of S-Enriched Surface of Cu2ZnSn(S,Se)4 Absorber and Band Gap Controlled (Zn,Sn)O Buffer

For high efficiency kesterite Cu2ZnSn(S,Se)4 (CZTSSe) solar cell, CdS thin film was usually used as a buffer layer. However, due to the toxicity of Cd and pollution problems involved from the solution-based chemical bath deposition, eco-friendly high efficiency CZTSSe solar cell with Cd-free buffer is necessary. As an Cd-free buffer layer, we investigated (Zn,Sn)O (ZTO) film deposited by sputtering method. In order to achieve high power conversion efficiency, we controlled energy band gaps of CZTSSe absorber as well as ZTO buffer, which was required to optimize conduction band offset (CBO) between the absorber and the buffer and to increase open circuit voltage (Voc) and fill factor (FF). The CBO was optimized by controlling the band gap of ZTO. By varying the Sn/(Zn + Sn) ratio and its deposition temperature, band gap of ZTO was successfully adjusted. Experimental and computational calculation results showed that solar cell performance was strongly affected by the CBO between absorber and buffer. Besides CBO matching, larger band gap of ZTO improved short circuit current density (Jsc) with enhanced external quantum efficiency value in blue photon spectrum range. As an additional way to improve power conversion efficiency of solar cell, band graded CZTSSe absorber was developed by using spray-based two-step process. The sprayed CZTSSe film was engineered to have S-enriched surface, which makes surface band gap widened and surface passivated, and resultantly increases Voc, Jsc and fill factor (FF). By controlling band gaps of both CZTSSe absorber and ZTO buffer, we obtained 11.22% environment-friendly CZTSSe solar cell without MgF2 anti-reflection coating.

(Zn↗

Simultaneous Overexpression of FERULOYL‐CoA 6′‐HYDROXYLASE 1 and COUMARIN SYNTHASE Leads to Coumarin‐Enriched Lignin and Improved Saccharification in Greenhouse‐ and Field‐Grown Poplar

ABSTRACT The urgent need for renewable resources has increased the interest in woody biomass to manufacture bio‐based products. However, lignin recalcitrance limits the enzymatic conversion of wood into fermentable sugars, posing a major challenge for biomass deconstruction. To address this problem, we aimed at incorporating the coumarin scopoletin into the lignin polymer of poplar ( Populus tremula × P . alba ) by expressing FERULOYL‐CoA 6′‐HYDROXYLASE 1 ( F6′H1 ) and COUMARIN SYNTHASE ( COSY ) in lignifying cells. Three constructs were evaluated: two bicistronic constructs, SCOP1 ( COSY followed by F6′H1 ) and SCOP2 ( F6′H1 followed by COSY ), and one monocistronic, SCOP3 (only F6′H1 ). SCOP1 poplars produced most free scopoletin without altering overall lignin, cellulose or hemicellulose content. SCOP2 poplars were overall less efficient in scopoletin production and most of these lines showed a severe biomass yield penalty, whereas SCOP3 caused plant lethality. NMR and metabolic analyses confirmed that scopoletin cross‐coupled with G and S monomers during lignification in SCOP1 lines. In addition to scopoletin, the detection of benzodioxane structures revealed the incorporation of dihydroxycoumarins. Overall coumarin incorporation in lignin amounted up to 2.3%. After alkaline pretreatment, wood from greenhouse‐grown SCOP1 poplars released up to 29% more glucose compared to the wild type upon limited saccharification. Field‐testing of three SCOP1 lines showed a 6 to 11% increase in saccharification efficiency, with the line containing the lowest scopoletin levels maintaining normal growth. These results demonstrate that engineering lignin composition in poplar can improve saccharification, and emphasize the importance of construct design, translational research and field validation.

alternative lignin monomers↗

Innovative Interfacial Engineering for Simultaneous Enhancement in Efficiency, Stability, and Reliability in Perovskite Devices

The overarching objective of this project was to increase significantly the mechanical adhesion toughness of the key interfaces in PSCs, thereby improving the durability and reliability of PSCs and minimodules, while simultaneously enhancing their PCE. This is achieved by incorporating rationally-chosen self-assembled monolayers (SAMs) at key PSC interfaces. Inherently scalable methods for the deposition of MHP light-absorber thin films and SAMs are employed to ensure a viable path towards manufacturability. Furthermore, detailed understanding of mechanisms of PSCs and minimodules degradation, and SAMs-induced mitigation, is provided. As part of the project accomplishments, >60% increase in the adhesion toughness of the key PSC interfaces over their SAMs-free control counterparts was achieved. Also, PCEs >20% and >19% in rigid and flexible, respectively, single-junction PSCs (~1 cm 2 area) were achieved. It was shown that <20% PCE loss in flexible PSCs with SAMs can be achieved after bend testing. It was demonstrated that T80 (80% retention of initial PCE) of >5,000 hours in rigid PSCs (~1 cm2 area) can be achieved. Comprehensive understanding of the degradation mechanisms in PSCs was obtained. These strategies were adopted towards developing minimodules. PCE of >21% was obtained in an 6-cm 2 area minimodule, with T91 of 1,000 hours.

14 SOLAR ENERGY↗

Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles

Off-road vehicles, such as wheel loaders, excavators, and harvesters, are extensively utilized across a wide range of industries, including construction, agriculture, and mining. These machines have become indispensable in supporting the day-to-day operational needs of a nation, playing a critical role in various sectors' infrastructure and productivity. However, despite their utility, off-road vehicles are significant consumers of fossil fuels, resulting in substantial emissions that contribute to environmental degradation. This highlights the pressing need for research and technological advancements aimed at improving their energy efficiency and reducing their carbon footprint. There are, however, two primary challenges that must be addressed to achieve these goals. First, off-road vehicles typically perform both driving and working tasks simultaneously, which introduces a high level of complexity into their overall dynamic systems. Analysis the interactions between these functions is challenging. Second, research into off-road vehicles is inherently interdisciplinary, demanding expertise across several domains such as fluid power systems, vehicle dynamics, control theory, optimization techniques, and real-world implementation. Recognizing these challenges, we proposed the project titled "Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles" as a comprehensive solution to enhance fuel efficiency while simultaneously improving productivity. This project specifically focuses on autonomous off-road vehicles, with particular attention to wheel loaders, and seeks to develop novel methods to optimize energy consumption without sacrificing operational performance. The project integrates real-time control algorithms, vehicle dynamics modeling, and co-optimization of powertrain system and vehicle system to achieve these goals. Our optimization strategy dynamically co-optimizes critical parameters at both the powertrain and vehicle levels, including vehicle speed, working tool movements, powertrain dynamics, and engine operations in real-time. To streamline this optimization process, we developed a vehicle model that captures the key dynamics while significantly enhancing computational efficiency. This allows the system to intelligently minimize fuel consumption, all while maintaining or even improving productivity through real-time calculations during various off-road operations. To validate the effectiveness of this energy optimization method, we introduced a state-of-the-art Hardware-in-the-Loop (HIL) testbed. This reconfigurable testbed seamlessly integrates the actual engine with virtual models of the wheel loader's subsystems, allowing for accurate emulation of real-world operational loads and environments. By simulating these conditions, the HIL testbed enables us to evaluate the wheel loader’s performance under diverse working scenarios, ensuring the developed solution is applicable in real-world operations. This testbed proved to be instrumental in validating the optimization algorithms and demonstrating the system's practical effectiveness. During the evaluation and testing phase, we employed the HIL testbed to rigorously assess the energy savings and productivity improvements generated by the optimized system. The results were highly encouraging, revealing that the automated wheel loader achieved over 30% fuel savings compared to traditional, human-operated cycles, with comparable or even enhanced levels of productivity. The insights gained from this HIL-based testing provided critical validation of our approach and highlighted the potential for deploying these optimized autonomous technologies in real-world off-road vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

Heterogeneous oxidation of hydrogen-natural gas blends in a safe, clean, and efficient burner design

The growth of hydrogen as an alternative clean fuel for fulfilling thermal energy needs of multiple economic sectors globally requires access to reliable, safe, energy efficient, emission free combustion technology. The work described in this short communication shows the applicability of a novel heterogeneous combustion design in utilizing a wide range of hydrogen blended methane concentrations to cleanly and safely generate thermal energy. The utilization of a simple first principles design approach along with engineered materials yielded a fuel-flexible hybrid infrared-convection burner design capable of lowering NOx emissions by more than 95% while simultaneously improving the heat transfer efficiency by 15% with a wide range of hydrogen concentrations. Here, the safety and performance of the combustion design was demonstrated in an burner at capacities of up to 12,000 Btu/h in producing temperatures of 900 °C. The atmospheric burner concept was integrated in a cooktop configuration with combined thermal power rating of 30,000 Btu/h and operated with hydrogen blended natural gas.

08 HYDROGEN↗

Surface engineering with oxidized Ti 3 C 2 T x MXene enables efficient and stable p-i-n-structured CsPbI 3 perovskite solar cells

All-inorganic CsPbI 3 perovskite has a near-ideal band gap, high thermal stability, and simple material composition, thus presenting a promising option for developing perovskite/Si tandem solar cells. However, CsPbI 3 undergoes a rapid phase transition under exposure to moisture and exhibits a significant performance gap relative to other perovskite compounds, particularly in the p-i-n structure favored for perovskite/Si tandems. In this work, we demonstrate highly efficient and stable p-i-n-structured CsPbI 3 perovskite solar cells by surface engineering the CsPbI 3 layer with oxidized Ti 3 C 2 T x MXene (OMXene) nanoplates via spray coatings. OMXene provides a physical barrier against moisture and improves charge separation at the perovskite-electron transporting layer interface via an enhanced electric field. Consequently, we demonstrated CsPbI 3 /OMXene-based p-i-n devices with efficiencies of 19.69% for 0.096-cm 2 cells and 14.64% for 25-cm 2 minimodules. The encapsulated minimodule showed good stability, retaining ~85% of the initial efficiency under simultaneous damp heat (85°C/85% relative humidity) and 1-sun light soaking for over 1,000 h.

14 SOLAR ENERGY↗

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges

Traffic intersections are crucial and challenging nodes in transportation networks where multiple lanes of vehicles and pedestrians converge. About one-quarter of traffic fatalities and about one-half of all traffic injuries in the United States happen at traffic intersections . Effective management of these intersections is important to ensure safety and efficiency of all users - vehicles, pedestrians, cyclists, and vulnerable road users (VRUs). With advancements in sensor perception technologies such as radar, light detection and ranging (lidar), and cameras, traffic intersections are developing into dynamic and data-rich environments. By using these data to create a real-time digital twin, we can enable real-time data-driven decision making and a range of applications such as sharing perception information to connected vehicles (CVs) and connected autonomous vehicles (CAVs), safety affirmative signaling, and curb optimizing to improve efficiency and enhance safety.This paper presents an overview of the concept and examines the challenges involved in implementing an infrastructure-based cooperative perception engine at a traffic intersection. In addition to outlining the physical components, this study also addresses important challenges involved in a multi-sensor system. We present results from deploying the National Renewable Energy Laboratory's (NREL's) Infrastructure Perception and Control (IPC) mobile trailer at a traffic intersection in the city of Colorado Springs, Colorado, USA that employed multiple radars and lidars to capture the data. This study provides necessary practical learning for the Cooperative Driving Automation (CDA) and traffic engineering communities for next-generation infrastructure-based cooperative perception that promises improvements in signal control for optimized traffic flow, among other applications, and documents findings for ongoing research and development efforts in other areas.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

Process intensification of CO 2 capture by low-aqueous solvent

Low-energy solvent-based CO 2 absorption processes have drawn attention as a next-generation post-combustion CO 2 capture technology to reduce CO2 emissions from fossil fuel– or biomass-fired power generation and industrial flue gas streams. A low-aqueous (or water-lean) solvent process may substantially reduce the thermal energy consumption for solvent regeneration. Low-aqueous solvent–based processes are thermally sensitive, requiring a delicate temperature control within the absorber because of the fast exothermic amine-CO 2 reaction and low heat capacity organic diluent. This reaction may result in heat accumulation in a packed absorption column and undesirable CO 2 desorption occurring as the solvent moves through the column, reducing the solvent’s CO 2 capture efficiency if its temperature is not controlled. Using a 3D printed intensified packing device, enhanced heat and mass transfer were demonstrated in an amine-CO 2 scrubbing process using low-aqueous solvent. The multifunctional intensified device facilitates contact of the reactive solvent and gas phases in a single stage and heat removal by a cooling fluid flowing through channels in the interior of the corrugated plates of the device. These functionalities led to effective thermal management along the column via intrastage cooling and significant improvement in CO 2 uptake under a wide range of operating conditions. Intrastage cooling effectively reduced the solvent average temperature along the column by ~10 °C and, as a result, the solvent’s capture efficiency improved by up to 25%.

42 ENGINEERING↗