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At least 73 records · Page 4

Generating multiple benefits from forests by producing value-added products: Lessons from the Pacific Northwestern US

This paper asks what conditions are needed to counteract a declining forest industry. The mobilization of supply chains for new value-added forest products and services can be supported by programs designed to simultaneously achieve multiple goals related to health, climate, and rural economic development. But several challenges are identified that underscore the need to stack benefits and incentives to achieve muti-sectoral goals. Based on a case study in Washington state, we find opportunities and constraints for sourcing forest products are determined by the local and regional conditions such as availability of working forests and their residues, socioeconomic conditions, workforce availability, transportation options, and perceptions about social license of the new industry. Key recommendations are the need for (1) a consistent demand and resilient supply chain for the new product; (2) a stable, supportive policy and assessment framework; (3) timely, transparent, and trusted monitoring and reporting of benefits and costs; (4) fostering engagement and buy-in from stakeholders; (5) a context-specific evaluation of opportunities and constraints; and (6) agreement on the goals of sustainable forestry. A diversity of products and markets builds a more resilient forest-based economy by mitigating impacts of disruptions in any individual market, adding value to biomass, increasing employment, and reducing forest risks to fire, insects, and disease.

Bioenergy↗

Poor reliability of public charging stations can impede the growth of the electric vehicle market

How does the reliability of public charging infrastructure affect electric vehicle (EV) adoption? Substantial public and private investments are expanding EV charging networks, but concerns are growing about the poor reliability of existing chargers and its potential impacts on EV adoption. Using data from a nationwide survey, we employ a choice model to quantify the effects of perceived charging reliability on Americans’ intentions to purchase new or used EVs. By randomly assigning participants to receive information characterizing public charging as either very reliable or very unreliable, we show a causal effect of reliability perceptions on EV purchase intentions. In conclusion, we find that differences in perceived reliability are equivalent to changing price by 32 % of purchasing budget or changing range by 366 miles, underscoring the importance of reliable public charging.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Assessment of integral models for non-Boussinesq lazy plumes using numerical simulations

Integral modelling of turbulent buoyant plumes is crucial for rapid predictions of plume characteristics. While the governing equations are typically derived using self-similarity and a Boussinesq approximation, these assumptions may not hold for plumes originating from finite-area sources with large density ratios. Here, this work evaluates the accuracy of integral-scale models for non-Boussinesq lazy plumes using high-fidelity numerical simulations of turbulent helium plumes. We analyse the plume kinematics by computing vertical fluxes, plume radius and radial profiles, establishing some disparities between common practice and physical accuracy. We identify how the definition of the plume radius changes the perception of the plume structure when the flow is not self-similar and derive a relationship between the flux-based and threshold-based definitions without requiring self-similarity. We then examine the plume dynamics by evaluating the source terms from the governing plume equations. Our results support neglecting diffusive and viscous effects but emphasise the importance of the mean pressure gradient, even in the self-similar regime. Two coefficients need to be modelled: the well-known entrainment coefficient and the lesser-known momentum correction coefficient, which is a correction required for the momentum equation to account for self-similar and slender approximations. The momentum correction coefficient is found to be approximately constant and slightly greater than the assumed value of 1. The standard entrainment coefficient models perform well up to a local Richardson number three times the asymptotic value but overpredict entrainment for larger Richardson numbers. We propose a correction using the known finite limit of entrainment at infinite Richardson number.

Meehan, Michael Alexander [Sandia National Laborat↗

Molecular Mass Growth Processes to Polycyclic Aromatic Hydrocarbons through Radical–Radical Reactions Exploiting Photoionization Reflectron Time-of-Flight Mass Spectrometry

Polycyclic aromatic hydrocarbons (PAHs) represent critical building blocks in molecular mass growth processes to carbonaceous nanoparticles, referred to as interstellar and circumstellar grains along with soot particles in astrophysical environments and combustion systems, respectively. Recent advancements on elucidating elementary steps to PAHs have utilized reactions of aromatic radicals, resonantly stabilized free radicals, and aliphatic radicals with closed shell hydrocarbons. However, the role of radical–radical reactions (RRRs) leading to PAHs has remained largely unexplored on the molecular level due to preceding experimental challenges in producing sufficiently high number densities of radical reactants for isomer-selective detection of products from bimolecular and termolecular reactions. This Account offers the latest developments in our knowledge on the mechanisms and pathways to PAHs via RRRs probed in a chemical microreactor at temperatures as high as 1600 K. Product preservation in a molecular beam coupled with synchrotron vacuum ultraviolet photoionization reflectron time-of-flight mass spectrometry and photoelectron photoion coincidence spectroscopy enabled isomer-selective detection of PAHs of up to three rings by their photoionization efficiency curves, which were fit with a linear combination of reference curves for identification. Experiments were combined with computational fluid dynamics modeling of the physicochemical processes in the microreactor, as well as high-level electronic structure calculations to reveal the reaction pathways of each system. Six distinct reaction mechanisms were discovered in this work: propargyl addition─benzannulation (PABA), methyl addition─ring expansion (MARE), cyclopentadienyl addition─naphthylization (CPAN), fulvenallenyl addition─cyclization─aromatization (FACA), benzyl addition─aromatization (BAA), and phenyl addition─pentacyclization (PAP). By systematically varying the number of carbon atoms in the radical reactants, molecular mass growth processes involving reactions between radicals with odd numbers of carbon atoms access aromatics carrying one, two, or three six-membered rings, whereas reactions between even- and odd-carbon-numbered radicals produce aromatics combining five- and six-membered rings. Our investigations reveal unconventional cycloadditions on excited state triplet surfaces, additions of radicals to low spin density carbon-centered radicals, spiroaromatic and fulvene-type intermediates, and highly strained bicyclic reaction intermediates, challenging current perceptions of PAH molecular mass growth processes. All of the listed mechanisms, except for FACA, feature endoergic reactions or barriers which lie above the separated reactants and therefore might be central to circumstellar environments of carbon-rich stars and planetary nebulae as their descendants, but they play no role in the gas phase of cold molecular clouds where temperatures as low as 10 K dominate. Altogether, this work provides detailed reaction mechanisms of PAH growth processes, advancing our knowledge of the chemistry of carbonaceous matter in the universe.

Addition reactions↗

Postfire Biogeochemical Processes: Implications to Source Water Quality in Fire-Influenced Watersheds

Forested watersheds are instrumental in providing purified and reliable water to millions of people worldwide. The changing climate has increased the frequency and severity of global fire events. Forested watersheds and their ecosystem functions are greatly disrupted during fire activity. Postfire concerns in forested watersheds include unpredictable and potentially simultaneous alterations in source water quality and hydro-biogeochemical processes. Here, the degree of fire severity can complexly modify water quality through the production of fire-transformed constituents on the burned forest floor (i.e., nutrients, metal(loid)s, dissolved organic matter, and the formation of disinfection byproducts). Correspondingly, fire severity and postfire rainfall patterns can refine hydro-biogeochemical processes that influence the transport of the fire-transformed constituents (i.e., vegetation function, soil structure, hydrological pathways, and microbial communities). Postfire alterations to water quality and hydro-biogeochemical processes introduce further complexity with varying temporal influence, which ranges from months to decades. As postfire water quality and watershed response research progresses, it is essential to homogenize interdisciplinary expertise to bridge knowledge gaps between fields ranging from forest ecology, hydrology, microbiology, and geochemistry. A multidisciplinary approach in wildfire research will facilitate a comprehensive perception of the diverse water quality risks associated with fire activity and mitigate fire concerns on a global level.

Disinfection Byproducts↗

In the Mix : A Workshop Merging Computational Chemistry and Electrochemistry Alongside Data Science

As chemistry expands to more complex and interdisciplinary areas, a new generation of diverse researchers must engage with science and learn effective cross-disciplinary collaboration and communication. To these ends, we designed and implemented In the Mix, a graduate student-led, two-day workshop for undergraduate students promoting collaborative science in the context of energy storage innovations. Here, the interactive workshop was designed for future and emerging researchers to gain hands-on experience with data science, computational chemistry, and electrochemistry techniques that are critical for developing materials for battery technologies. Participants also visited commercial renewable energy facilities to help them connect discovery-based research with industry and broader societal considerations. The workshop content and structure ensured that participants experienced the interrelatedness of the fields and understood the importance of collaborative research to yield scientific advances with real-world applications. An external team evaluated the workshop and participants’ perceptions of their experiences. While our research context was energy storage, the workshop goals and outcomes are applicable to other contexts. Interdisciplinary, experiential workshops are a key avenue to broadening participation in science and research, and the ideas presented here can be readily modified for other scientific contexts and/or incorporated as broader impact activities.

25 ENERGY STORAGE↗

Comparative Analysis of Report-Back of Research Results Strategies for Personal Chemical Exposure Data

Background. Report-back of research results (RBRR) is ethically supported and highly requested by participants yet lacks broadly transferable guidelines for RBRR. Effective RBRR must be responsive to target audience needs and may not be addressed by a ‘one-size-fits-all’ approach. Objective. Within a subset of our 19 studies on RBRR, we had the unique opportunity to carry out a comparative analysis of RBRR strategies across cohorts with similar development and evaluation methods, yet distinct in life stage, geography, number and type of chemicals assessed, and community contexts. Methods. We highlight key outcomes from three environmental health studies: an ongoing New York, NY cohort (Fair Start; n=486) and a Detroit, MI cohort (CLEAR; n=34) assessing exposure to ambient urban pollution during pregnancy, and a longitudinal cohort in Houston, TX (Houston-3H) following Hurricane Harvey (n=312). Focus group and survey data were analyzed to identify lessons learned and explore how RBRR supports understanding of environmental health. Results. Commonalities emerged in RBRR development, design, organization, and data visualization, as well as in how RBRR can contribute to an understanding of health-environment connections. Differences included preferences for individual versus community level findings, as well as distinguishable contextual considerations. For pregnancy cohorts, messaging was framed with cultural sensitivity, and to avoid unintended consequences of parental guilt due to prenatal exposures. In the post-disaster Houston-3H study, participants requested additional transparency regarding sampling design and study rationale. Significance. All RBRR case studies reported chemicals without known regulatory or health guidelines, so results were contextualized within the study population. Participants across cohorts requested multi-study comparisons to better understand their results beyond their communities. While foundational RBRR elements (e.g. plain language, graphic organizers) may supersede cohort-specific differences, RBRR should be personalized to encompass perceptions of health across different life-stage, cultural, and environmental contexts.

Vogel, Taylor J.↗

Observation of early events in the photoactivation of Myxobacterial phytochrome using time-resolved serial femtosecond crystallography

Myxobacteria are non-photosynthetic, soil-dwelling bacteria distinguished by a multicellular stage in their life cycle known as fruiting bodies that are stimulated by light. Myxobacterial phytochromes are candidates for the perception of red-light. The mechanism how light is perceived and converted to a physiological response is unknown. Here, time-resolved serial femtosecond crystallographic (TR-SFX) experiments were conducted on microcrystals of the photosensory core module of the Stigmatella aurantiaca bacteriophytochrome 2 (SaBphP2). Initial events of the Z to E isomerization reaction of the covalently bound, open-chain tetrapyrrole biliverdin (BV) chromophore were determined. At 3 ps after light activation, the BV ring-D assumes a configuration needed for the isomerization. At 100 ps, a mixture of BV in the Z or E configuration is observed in subunit A, while in the other subunit the chromophore remains in the Z configuration. In conjunction with prior results, these structures reveal the molecular mechanism of phytochrome activation in the photomorphogenesis of the myxobacteria and provide the molecular foundation for physiological responses to red light in other bacteria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unconventional gas-phase synthesis of biphenyl and its atropisomeric methyl-substituted derivatives

The biphenyl molecule (C 12 H 10 ) acts as a fundamental molecular backbone in the stereoselective synthesis of organic materials due to its inherent twist angle causing atropisomerism in substituted derivatives and in molecular mass growth processes in circumstellar environments and combustion systems. Here, we reveal an unconventional low-temperature phenylethynyl addition–cyclization–aromatization mechanism for the gas-phase preparation of biphenyl (C 12 H 10 ) along with ortho-, meta-, and para-substituted methylbiphenyl (C 13 H 12 ) derivatives through crossed molecular beams and computational studies providing compelling evidence on their formation via bimolecular gas-phase reactions of phenylethynyl radicals (C 6 H 5 CC, X 2 A 1 ) with 1,3-butadiene-d 6 (C 4 D 6 ), isoprene (CH 2 C(CH 3 )CHCH 2 ), and 1,3-pentadiene (CH 2 CHCHCHCH 3 ). The dynamics involve de-facto barrierless phenylethynyl radical additions via submerged barriers followed by facile cyclization and hydrogen shift prior to hydrogen atom emission and aromatization to racemic mixtures (ortho, meta) of biphenyls in overall exoergic reactions. Furthermore, these findings not only challenge our current perception of biphenyls as high temperature markers in combustion systems and astrophysical environments, but also identify biphenyls as fundamental building blocks of complex polycyclic aromatic hydrocarbons (PAHs) such as coronene (C 24 H 12 ) eventually leading to carbonaceous nanoparticles (soot, grains) in combustion systems and in deep space thus affording critical insight into the low-temperature hydrocarbon chemistry in our universe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗

The approximate second order coupled-cluster method based on a size-consistent Brillouin–Wigner partitioning

We present a variant of the approximate second order coupled-cluster method (CC2) with a two-parameter size-consistent Brillouin–Wigner (BW-s) partitioning instead of a Møller–Plesset (MP) partitioning for the unperturbed Hamiltonian, which we refer to as BWs-CC2. The computational complexity of this model scales identically to CC2 with molecular size. Conventional CC2 and its regularized BWs-CC2 variants, as well as conventional MP2 and two of its regularized BW-s2 variants, were assessed on a 535 element database spanning thermochemistry, non-covalent interactions, barrier heights, and isomerization energies. To ensure a well-defined model chemistry, the assessment was performed using internally stable spin-polarized Hartree–Fock (HF) orbitals in the finite aug-cc-pVQZ basis without counterpoise corrections. As a result of using stable orbitals, contrary to conventional wisdom, we find that CC2 substantially outperforms MP2 on molecules with significantly spin contaminated reference orbitals without a significant increase in error on systems with a spin-pure reference, showing the value of its single substitutions. While no single choice of regularization parameters can be optimal for all datasets, we find that BWs-CC2 generally outperforms both CC2 and BW-s2 with a single judicious parameter choice. Additional tests on dipole moments and bond lengths of diatomics provide further support for the utility of this choice. Furthermore, the main outliers and poorest performing cases are associated with large amounts of spin-contamination in the HF reference, which is indicative of systems with either strong correlation or extensive artificial symmetry breaking. Overall, these findings argue that the perception of the quality of the CC2 ground state should be reevaluated and that it can be further improved upon by the soundly based BWs-CC2 variant with the recommended parameter choice.

Correlation energy↗

Convergent evolution of NFP -facilitated root nodule symbiosis

The origin and phylogenetic distribution of symbiotic associations between nodulating angiosperms and nitrogen-fixing bacteria have long intrigued biologists. Recent comparative evolutionary analyses have yielded alternative hypotheses: a multistep pathway of independent gains and losses of root nodule symbiosis vs. a single gain followed by numerous losses. A detailed reconstruction of the history of genes involved in signaling between nitrogen-fixing bacteria and potential hosts, particularly lipo-chitooligosaccharide (LCO) signaling, is needed to distinguish between these hypotheses. LCO recognition by plants involves the Nod Factor Perception ( NFP ) gene family; in the legume model Medicago truncatula (Fabales), MtNFP is essential for establishing rhizobial symbiosis. Here, we document convergent evolution of NFP , indicating multiple origins of LCO-driven symbiosis. In contrast to previous models that explain the recruitment of NFP via a single duplication in the ancestor of the nitrogen-fixing clade, our phylogenomic and synteny results suggest this duplication does not span the entire clade. Tandem duplication in a common ancestor of Cucurbitales and Rosales resulted in the NFP1 and NFP2 groups. In contrast, the phylogenetically closest paralog of MtNFP is MtLYR1 , located on a different chromosome within a large syntenic block. All available data indicate that a large-scale duplication resulted in MtNFP and MtLYR1 , likely corresponding to a whole-genome duplication in an ancestor of subfamily Papilionoideae of Fabaceae. We show that MtNFP and the NFP2 -like group are not orthologous, indicating multiple independent gains of NFP -based LCO signaling. This molecular convergence provides a possible mechanism for multiple gains of root nodule symbiosis across the nitrogen-fixing clade.

LCO signaling↗

Forecasting fluid-injection induced seismicity to choose the best injection strategy for safety and efficiency

Induced seismicity poses a challenge to the development of Enhanced Geothermal Systems (EGS). Improving monitoring and forecasting techniques is essential to mitigate induced seismicity and thereby fostering a positive perception of EGS projects among local authorities and population. Induced seismicity is the result of complex and coupled thermo-hydro-mechanical-chemical mechanisms. Injection flux and pressure are crucial controlling parameters for both hydraulic stimulation and circulation protocols. We develop a methodology combining a hydro-mechanical model with a seismicity rate model to estimate the magnitude and frequency of mainshocks and aftershocks induced by fluid injection. We apply the methodology to the case of the Basel EGS (2006, Switzerland) to compare the effects of progressive, cyclic and constant injections on the mechanical response of discrete faults. Results from the coupled hydro-mechanical models show that the pore pressure diffusion and consequent enhancement of fault permeability are limited to the vicinity of the injection well during cyclic injection. Additionally, constant injection induces seismicity from the start of the injection but enhances the permeability of most of the faults within a shorter duration, inducing less post-injection seismicity. The methodology can be adapted to any numerical model and allows new projects to be developed by anticipating the safest injection protocol. This article is part of the theme issue ‘Induced seismicity in coupled subsurface systems’.

58 GEOSCIENCES↗

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

Constitutive and inducible oleoresin defenses share genetic architectures and mechanisms in Pinus taeda

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

genome-wide association study↗

Scalable Bayesian Physics-Informed Kolmogorov-Arnold Networks

Uncertainty quantification (UQ) plays a pivotal role in scientific machine learning, especially when surrogate models are used to approximate complex systems. Although multilayer perceptions (MLPs) are commonly employed as surrogates, they often suffer from overfitting due to their large number of parameters. Kolmogorov-Arnold networks (KANs) offer an alternative solution with fewer parameters. However, gradient-based inference methods, such as Hamiltonian Monte Carlo (HMC), may result in computational inefficiency when applied to KANs, especially for large-scale datasets, due to the high cost of back-propagation. To address these challenges, we propose a novel approach, combining the dropout Tikhonov ensemble Kalman inversion (DTEKI) with Chebyshev KANs. This gradient-free method effectively mitigates overfitting and enhances numerical stability. In addition, we incorporate the active subspace method to reduce the parameter-space dimensionality, allowing us to improve the accuracy of predictions and obtain more reliable uncertainty estimates. Extensive experiments demonstrate the efficacy of our approach in various test cases, including scenarios with large datasets and high noise levels. Our results show that the new method achieves comparable or better accuracy, much higher efficiency as well as stability compared to HMC, in addition to scalability. Moreover, by leveraging the low-dimensional parameter subspace, our method preserves prediction accuracy while substantially reducing further the computational cost.

97 MATHEMATICS AND COMPUTING↗

From carbon to climate action: harnessing basalt for geological carbon dioxide (CO 2 ) storage onshore and offshore

Abating emissions and reducing atmospheric concentrations of carbon dioxide (CO 2 ) are crucial in avoiding catastrophic climate change. Basalt reservoirs offer suitable CO 2 storage sites and are present onshore and offshore. This study compares the geological, economic and social aspects of CO 2 storage in both domains using two basalt formations from the Republic of Ireland: the Limerick Igneous Suite and the Druid Formation. Offshore reservoirs offer larger storage resources but are more expensive to develop. Nevertheless, both offer gigatonne-scale theoretical CO 2 storage. Reviewing public perception studies on wind energy demonstrates that the commonly held belief that offshore projects face less opposition owing to their distance from communities has been dispelled, while similar studies on carbon capture and removal show no preference for onshore or offshore development. Instead, a general scepticism towards carbon removal is observed, with concerns that it hinders broader decarbonization efforts. The desire of all stakeholders to be involved throughout project development is consistently observed. Lessons from offshore natural gas projects highlight the consequences of failing to engage with local communities. The Republic of Ireland has significant potential to deploy geological CO 2 storage in basalt reservoirs, but policy hurdles such as legal limits on storage volumes must be overcome to reconcile climate ambition and legislative capacity.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗

FiberFlex: Real-time FPGA-based Intelligent and Distributed Fiber Sensor System for Pedestrian Recognition

In recent years, security monitoring of public places and critical infrastructure has heavily relied on the widespread use of cameras, raising concerns about personal privacy violations. To balance the need for effective security monitoring with the protection of personal privacy, we explore the potential of optical fiber sensors for this application. This article proposes FiberFlex, an intelligent and distributed fiber sensor system. Ultizing Field Programmable Gate Arrays (FPGA) high-level synthesis (HLS) acceleration, FiberFlex offers real-time pedestrian detection by co-designing the entire pipeline of optical signal acquisition, processing, and recognition networks based on the principles of optical fiber sensing. As a promising alternative to traditional camera-based monitoring systems, FiberFlex achieves pedestrian detection by analyzing the vibration patterns caused by pedestrian footsteps, enabling security monitoring while preserving individual privacy. FiberFlex comprises three modules: First , fiber-optic sensing system: A fiber-optic distributed acoustic sensing (DAS) system is built and used to measure the ground vibration waves generated by people walking. Second , algorithms: We first collect the training data by measuring the ground vibration waves, label the data, and use the data to train the neural network models to perform pedestrian recognition. Third , hardware accelerators: We use HLS tools to design hardware modules on FPGA for data collection and pre-processing and integrate them with the downstream neural network accelerators to perform in-line real-time pedestrian detection. The final detection results are sent back from FPGA to the host CPU. We implement our system FiberFlex with the in-house built DAS system and AMD/Xilinx Kintex7 FPGA KC705 board and verify the whole system using the real-world collected data. We conduct recognition tests on five test subjects of varying ages, heights, and weights in a fixed sensing area. Each subject experienced 20 real-time recognition tests using their daily walking habits, and the subjects were given adequate rest between tests. After 100 tests on five test subjects, the overall real-time recognition accuracy exceeded \(88.0\%\) . The whole system uses 55 W of power, 33 W in the optical DAS system and 22 W in the FPGA. Relying on its end-to-end interdisciplinary design, FiberFlex seamlessly combines fiber-optic sensors with FPGA accelerators to enable low-power real-time security monitoring without compromising privacy, making it a valuable addition to the existing security monitoring network. According to FiberFlex, more valuable research can be conducted in the future, such as fall monitoring for the elderly, migration of identification networks between different application scenarios, and improvement of anti-interference performance in more complex environments. In future perception networks, where the “eyes” are not feasible, let’s use fiber optic touch instead.

Distributed↗