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At least 757 records · Page 42

A high efficiency rooftop air conditioning system using multi-speed compressors

This study delineates a meticulous exploration of technologies to enhance the energy efficiency of rooftop air conditioning units, employing the DOE/ORNL heat pump design model for comprehensive engineering design and optimization. A baseline rooftop air conditioning unit, featuring a 13 ton (45.7 kW) cooling capacity and a 17.9 integrated energy efficiency ratio, served as the point of departure for substantive efficiency enhancements. Key modifications included the consolidation of two refrigerant circuits into one, integrating three parallel 2-stage (dual-speed) compressors, fan replacements with high-efficiency substitutes. Notably, a lower global warming potential refrigerant, R452B, was evaluated as a substitute for R-410A, demonstrating better performance in the lab prototype. Further, the achieved measured integrated energy efficiency ratio of 21.4 in the lab prototype surpassed the baseline integrated energy efficiency ratio. Comparative evaluations between R410A and R452B indicated heightened efficiency with the latter, showcasing a lab-demonstrated integrated energy efficiency ratio of 22.4 at the rated capacity of 13.8 ton (48.5 kW) and 23.9 integrated energy efficiency ratio at the rated capacity of 10 ton (35.2 kW). This research underscores the successful development of a rigorous, energy efficient rooftop air conditioning unit prototype with noteworthy environmental and economic implications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Study of CMOS strip sensor for future silicon tracker

Monolithic silicon sensors developed with High-Voltage CMOS (HV-CMOS) processes have become highly attractive for charged particle tracking. Compared with the standard CMOS sensors, HV-CMOS sensors can provide larger and deeper depletion regions that lead to larger signals and faster charge collection. They can provide high position resolution, low material budget, high radiation hardness and low cost that are desirable for high performance tracking in harsh collision environment. Various studies have been conducted to explore the technology feasibility for the large-area tracking systems at future collider experiments. CHESS (CMOS HV/HR Evaluation for Strip Sensor) sensor series have been developed as an alternative solution to the conventional silicon micro-strip detectors for the ATLAS inner tracker upgrade. The first prototype (named CHESS1) was to evaluate the diode geometry and the in-pixel analog electronics. Obtained test results were used to optimize the second prototype (named CHESS2). CHESS2 was implemented with a full digital readout architecture and realized as a full reticle sized monolithic sensor. Here, the basic characteristics of the CHESS2 prototype sensors and their performance in response to different input signals are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

PICOSEC-Micromegas Detector, an innovative solution for Lepton Time Tagging

The PICOSEC-Micromegas (PICOSEC-MM) detector is a novel gaseous detector designed for precise timing resolution in experimental measurements. It eliminates time jitter from charged particles in ionization gaps by using extreme UV Cherenkov light emitted in a crystal, detected by a Micromegas photodetector with an appropriate photocathode. The first single-channel prototype tested in 150 GeV/c muon beams achieved a timing resolution below 25 ps, a significant improvement compared to standard Micropattern Gaseous Detectors (MPGDs). This work explores the specifications for applying these detectors in monitored neutrino beams for the ENUBET Project. Key aspects include exploring resistive technologies, resilient photocathodes, and scalable electronics. New 7-pad resistive detectors are designed to handle the particle flux. In this paper, two potential scenarios are briefly considered: tagging electromagnetic showers with a timing resolution below 30ps in an electromagnetic calorimeter as well as individual particles (mainly muons) with about 20ps respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Universal Nuclear Accident Dosimeter

The Lawrence Livermore National Laboratory (LLNL) Universal Nuclear Accident Dosimetry (UNAD) project is a four-year initiative aimed at advancing nuclear accident dosimetry methods. This article presents an overview of the research, key findings, and the progress made throughout the project. The primary goals included a background into the history of nuclear accident dosimetry, consolidating current dosimetry techniques within the NNSA/DOE complex, fostering collaboration among subject matter experts, and exploring novel technologies for potential implementation. The technical focus centered on investigating new and novel technologies, instrumentation methods, and analysis methods to develop recommendations for a potential nuclear accident dosimeter (NAD) to be universally deployed through the DOE complex. A multilaboratory and multinational Usergroup was established, conducting periodic meetings to facilitate knowledge exchange. The UNAD team has participated in two international nuclear accident dosimetry intercomparison exercises and one characterization exercise, where the existing LLNL NAD and a prototype alanine electron paramagnetic dosimeter NAD were deployed. Ongoing improvements are being made to the prototype NAD based on results from the exercises, laboratory studies, and collaboration with other laboratories. A machine learning algorithm to optimize the geometry and conversion factors of the current LLNL NAD is being implemented, and the resulting design will be tested in the next exercise. In conclusion, key lessons learned and future directions for the project are discussed.

Electron paramagnetic resonance spectroscopy↗

Potential Adoption and Benefits of Co-Optimized Multimode Engines and Fuels for U.S. Light-Duty Vehicles

Exploring a diverse portfolio of technologies for decarbonization is crucial to understanding the potential impacts of different technological solutions and their associated environmental implications. Using high-octane, high-sensitivity biofuel blends in co-optimized multimode engines can increase engine efficiency and reduce vehicle emissions. Here, the multimode engine research focuses on the benefits of light-duty vehicle engines, which can operate in multiple modes depending on the vehicle's load. Low-temperature combustion can improve efficiency and reduce emissions (such as those from oxides of nitrogen and particulate matter) during low-load operation, while spark ignition performance is maintained in high-load operation. These advanced engines can be optimized to run on blends of biobased fuels. This analysis models scenarios for potential market adoption of co-optimized multimode vehicles fueled by three different bioblendstocks: ethanol, isopropanol, and isobutanol. An integrated modeling approach is used to forecast the energy and environmental impacts of the deployment of co-optimized multimode vehicles and fuels in the light-duty sector over the 2020-to-2050 time horizon. The multidisciplinary approach combines vehicle sales modeling, system dynamics modeling of the biorefining industry, and life cycle assessment to estimate the emissions and energy benefits. The models consider market forces such as consumer preferences for vehicle attributes, biofuel supply and demand dynamics subject to biorefinery capacity build-out and bioresource constraints, and forecasted changes to the U.S. bulk energy system over time. Market adoption of co-optimized vehicles is evaluated across a wide parameter space for incremental vehicle cost and engine efficiency improvement. This analysis reveals that the deployment of co-optimized multimode fuels and vehicles results in up to a 5% reduction in annual sector-wide life cycle greenhouse gas (GHG) emissions by 2050, relative to a business-as-usual scenario, but is also indicates environmental trade-offs, such as higher life cycle water-use. Emission benefits could potentially increase beyond 2050, as the new technologies penetrate the market and gain a foothold. Results also show that, under certain circumstances, vehicles with engines co-optimized for use with high-octane, high-sensitivity biofuel blends can be cost-competitive with conventional gasoline, while reducing GHG emissions. Our modeling results indicate that co-optimized multimode fuels and engines can be strategically leveraged in tandem with electrification to decarbonize the light-duty sector. Co-optimized vehicles could play a role in the early years of the time horizon, while electric vehicles (EVs) could become more competitive in the later years, highlighting the complementary benefits of these technologies for GHG reductions.

Oke, Doris↗

Insights into the Structure and Dynamics of Metal–Organic Frameworks via Transmission Electron Microscopy

Metal–organic frameworks (MOFs) are hybrid materials composed of metal ions and organic linkers featuring high porosity, crystallinity, and chemical tunability at multiple length scales. Here, a recent advancement in transmission electron microscopy (TEM) and its direct application to MOF structure–property relationships have changed how we consider rational MOF design and development. Herein, we provide a perspective on TEM studies of MOFs and highlight the utilization of state-of-the-art TEM technologies to explore dynamic MOF processes and host–guest interactions. Additionally, we provide thoughts on what the future holds for TEM in the study of MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation of low-energy particle remnants in high-energy collisions at the LHC with a skipper-CCD detector

We deployed the Mobile Skipper Testing Apparatus ∼33 m away from the Compact Muon Solenoid collision point, the first skipper-CCD detector probing low-energy particles produced in high-energy collisions at the Large Hadron Collider. In this work, we search for beam-related events using data collected in 2024 during beam-on and beam-off periods. The dataset corresponds to integrated luminosities of 113.3 fb −1 and 1.54 nb −1 for the proton-proton and Pb-Pb collision periods, respectively. We report observed event rates in a model-independent framework across two ionization regions: ≤ 20⁢𝑒 − and > 20⁢𝑒 − . For the low-energy region, we perform a likelihood analysis to test the null hypothesis of no beam-correlated signal. We found no significant correlation during proton-proton and Pb-Pb collisions. For the high-energy region, we present the energy spectra for both collision periods and compare event rates for images with and without luminosity. We observe a slight increase in the event rate following the Pb-Pb collisions, coinciding with a rise in the single-electron rate, which will be investigated in future work. Using the low-energy proton-proton results, we place 95% confidence level constraints on the mass-millicharge parameter space of millicharged particles. Overall, the results in this work demonstrate the viability of skipper-CCD technology to explore new physics at high-energy colliders and motivate future searches with more massive detectors.

Cervantes-Vergara, Brenda A. [Fermi National Accel↗

Opportunities and challenges to study solar neutrinos with a Q-Pix pixel readout

The study of solar neutrinos presents significant opportunities in astrophysics, nuclear physics, and particle physics. However, the low-energy nature of these neutrinos introduces considerable challenges to isolate them from background events, requiring detectors with low-energy threshold, high spatial and energy resolutions, and low data rate. We present the study of solar neutrinos with a kiloton-scale liquid argon detector located underground, instrumented with a pixel readout using the Q-Pix technology. We explore the potential of using volume fiducialization, directional topological information, light signal coincidence, and pulse-shape discrimination to enhance solar neutrino sensitivity. We find that discriminating neutrino signals below 5 MeV is very difficult. However, we show that these methods are useful for the detection of solar neutrinos when external backgrounds are sufficiently understood and when the detector is built using low-background techniques. When building a workable background model for this study, we identify 𝛾 background from the cavern walls and from capture of 𝛼 particles in radon decay chains as both critical to solar neutrino sensitivity and significantly underconstrained by existing measurements. Finally, we highlight that the main advantage of the use of Q-Pix for solar neutrino studies lies in its ability to enable the continuous readout of all low-energy events with minimal data rates and manageable storage for further off-line analyses.

multi-purpose particle detectors↗

Harnessing Virtual Power Plants Reliably: Enabling tools for increased observability, controllability, operation, and aggregation of distributed energy resources

Harnessing virtual power plants enhances the integration of distributed energy resources into utility grids for a sustainable energy future. Virtual power plants (VPPs) aggregate DERs to enhance resource adequacy and reduce emissions. U.S. utilities are exploring various technologies to manage DERs effectively. FERC Order 2222 allows DERs to participate in both wholesale and retail markets. Enhancing observability and controllability of behind-the-meter (BTM) DERs is essential for reliable grid operations. A hierarchical control architecture can improve coordination among residential energy resources. Field tests showed nearly 20% energy savings and 30% peak power reduction during grid events. Effective management of DERs requires enhanced situational awareness to prevent grid congestion. Integrating DER management systems (DERMS) with existing planning tools can improve operational security. Near-real-time grid models can validate optimal resource set points against resource uncertainty. Traditional uninterruptible power supplies (UPS) can be upgraded to support grid services and become part of VPPs. Upgrading UPS systems can reduce costs by 75% and unlock significant battery capacity. New battery management systems and grid-aware controllers are essential for optimizing UPS performance. Continued research and development are necessary to address challenges in integrating DERs into utility grids. Encouraging customer participation in pilot programs is vital for the evolution of VPPs. Here, the shift towards price-responsive DERs and VPPs is expected to enhance energy distribution efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Adaptive Circuit Learning for Quantum Metrology

Quantum sensing is an important application of emerging quantum technologies. We explore whether a hybrid system of quantum sensors and quantum circuits can surpass the classical limit of sensing. In particular, we use optimization techniques to search for encoder and decoder circuits that scalably improve sensitivity under given application and noise characteristics. Furthermore, our approach uses a variational algorithm that can learn a quantum sensing circuit based on platform-specific control capacity, noise, and signal distribution. The quantum circuit is composed of an encoder which prepares the optimal sensing state and a decoder which gives an output distribution containing information of the signal. We optimize the full circuit to maximize the Signal-to-Noise Ratio (SNR). Furthermore, this learning algorithm can be run on real hardware scalably by using the "parameter-shift" rule which enables gradient evaluation on noisy quantum circuits, avoiding the exponential cost of quantum system simulation. We demonstrate up to 13.12x SNR improvement over existing fixed protocol (GHZ), and 3.19x Classical Fisher Information (CFI) improvement over the classical limit on 15 qubits using IBM quantum computer. More notably, our algorithm overcomes the decreasing performance of existing entanglement-based protocols with increased system sizes.

42 ENGINEERING↗

A Novel Method for Preoperative Positioning of Total Ankle Replacement Using 3D Digital Model

Abstract Objective To establish a digital model of the ankle joint through 3D imaging technology and explore the preoperative placement of ankle replacement prostheses. Methods Computed tomography images of intact ankle joints from 54 cases in the outpatient and inpatient departments of our hospital were collected; according to the INBONE® total ankle system surgery process, the surgery model and surgical osteotomy were finished using MIMICS based on computer simulation method. The shortest distance was measured between the center point and the anterior, posterior, medial, and lateral, respectively, to ensure the precise position of the ankle replacement prosthesis by digital simulation surgery. The relationship between the two variables was analyzed by bivariate correlation analysis. Results The dataset of this study included 48 cases of the sub‐data set (26 males and 22 females) and included 27 cases of left ankle and 21 cases of right ankle. The average medial malleolar angle was 18.67°± 2.87°, the average amount of bone resection was 12.13 ± 1.86 cm 3 , the mid‐anterior distance was 1.72 ± 0.19 cm, the mid‐posterior distance was 2.00 ± 0.19 cm, the ratio of mid‐anterior to mid‐posterior was 0.87, the mid‐medial distance was 1.26 ± 0.17 cm, the mid‐lateral distance was 1.19 ± 0.16 cm, and the ratio of mid‐medial to mid‐lateral was 1.06. After osteotomy, the anteroposterior diameter was 3.73 ± 0.32 cm, the transverse diameter was 2.46 ± 0.27 cm, and the ratio of anteroposterior diameter to transverse diameter was 1.53. In the bottom view, the shape after osteotomy is rectangular. The mid‐anterior distance was strongly negatively correlated with age, the mid‐anterior distance and the amount of bone resection, the mid‐medial distance and the amount of bone resection, the mid‐lateral distance and the amount of bone resection, the mid‐lateral distance and the anteroposterior diameter, the anteroposterior diameter and the transverse diameter were all strongly positively correlated. Conclusion The projection point of the lower tibia centerline on the tibial horizontal osteotomy surface is located at a position slightly anterior to the midpoint of the transverse diameter after ankle arthroplasty. The rational positioning of the total ankle replacement is located at both a position slightly anterior to the midpoint of the transverse diameter and midpoint of the anteroposterior diameter, which can be used as a reference method before total ankle arthroplasty surgery.

Wu, Shi‐xun↗

CONTROLLED END GAS AUTO IGNITION WITH EXHAUST GAS RECIRCULATION ON A STOICHIOMETRIC, SPARK IGNITED, NATURAL GAS ENGINE

The goal of this study is to address fundamental limitations to achieving diesel-like efficiencies in heavy duty on-highway natural gas (NG) engines. Engine knock and misfire are barriers to pathways leading to higher efficiency engines. This study explores enabling technologies for development of high efficiency stoichiometric, spark ignited, natural gas engines. These include design strategies for fast and stable combustion and higher dilution tolerance. Additionally, advanced control methodologies are implemented to maintain stable operation between knock and misfire limits. To implement controlled end- gas autoignition (C-EGAI) strategies a Combustion Intensity Metric (CIM) is used for ignition control with the use of a Woodward large engine control module (LECM). Tests were conducted using a single cylinder, variable compression ratio, cooperative fuel research (CFR) engine with baseline conditions of 900 RPM, engine load of 800 kPa indicated mean effective pressure (IMEP), and stoichiometric air/fuel ratio. Exhaust gas recirculation (EGR) tests were performed using a custom EGR system that simulates a high pressure EGR loop and can provide a range of EGR rates from 0 to 40%. The experimental measurements included the variance of EGR rate, compression ratio, engine speed, IMEP, and CIM. These five variables were optimized through a Modified Box- Benken design Surface Response Method (RSM), with brake efficiency as the merit function. A positive linear correlation between CIM and f-EGAI was identified. Consequently, CIM was used as the feedback control parameter for C-EGAI. As such, implementation of C-EGAI effectively allowed for the utilization of high EGR rates and CRs, controlling combustion between a narrower gap between knock and lean limits. The change from fixed to parametric ignition timing with CIM targeted select values of f-EGAI with an average coefficient of variance (COV) of peak pressure of 5.4. The RSM efficiency optimization concluded with operational conditions of 1080 RPM, 1150 kPa IMEP, 10.55:1 compression ratio, and 17.8% EGR rate with a brake efficiency of 21.3%. At this optimized point of peak performance, a f-EGAI for C-EGAI was observed at 34.1% heat release due to auto ignition, a knock onset crank angle value of 10.3° aTDC and ignition timing of - 24.7° aTDC. This work has demonstrated that combustion at a fixed f-EGAI can be maintained through advanced ignition control of CIM without experiencing heavy knocking events.

Cooperative Fuel Research Engine, Auto Ignition, E↗

Q-BEEP: Quantum Bayesian Error Mitigation Employing Poisson Modeling over the Hamming Spectrum

Quantum computing technology has grown rapidly in recent years, with new technologies being explored, error rates being reduced, and quantum processor’s qubit capacity growing. However, near-term quantum algorithms are still unable to be induced without compounding consequential levels of noise, leading to non-trivial erroneous results. Quantum Error Correction (in-situ error mitigation) and Quantum Error Mitigation (post-induction error mitigation) are promising fields of research within the quantum algorithm scene, aiming to alleviate quantum errors, increasing the overall fidelity and hence the overall quality of circuit induction. Earlier this year, a pioneering work, namely HAMMER, published in ASPLOS-22 demonstrated the existence of a latent structure regarding post-circuit induction errors when mapping to the Hamming spectrum. However, they intuitively assumed that errors occur in local clusters, and that at higher average Hamming distances this structure falls away. In this work, we show that such a correlation structure is not only local but extends certain non-local clustering patterns which can be precisely described by a Poisson distribution model taking the input circuit, the device run time status (i.e., calibration statistics) and qubit topology into consideration. Using this quantum error characterizing model, we developed an iterative algorithm over the generated Bayesian network state-graph for post-induction error mitigation. Thanks to more precise modeling of the error distribution latent structure and the new iterative method, our Q-Beep approach provides state of the art performance and can boost circuit execution fidelity by up to 234.6% on Bernstein-Vazirani circuits and on average 71.0% on QAOA solution quality, using 16 practical IBMQ quantum processors. For other benchmarks such as those in QASMBench, the fidelity improvement is up to 17.8%. Q-Beep is a light-weight post-processing technique that can be performed offline and remotely, making it a useful tool for quantum vendors to integrate and provide more reliable circuit induction results.

Stein, Samuel A.↗

Extending High-Level Synthesis with AI/ML Methods

Artificial Intelligence (AI) and Machine Learning (ML) methods provide significant opportunities of improving quality of results when performing high-level synthesis (HLS). For example, they can be used to model and predict metrics of the final design (e.g., area, considering aspects such as interconnect overhead for different device technologies), facilitating exploration when searching for the best design trade-offs. They can also enable identifying hidden correlations across the various phases of the synthesis and the various optimizations performed, identifying the most effective pipelines. Finally, in more general terms, bio-inspired heuristic algorithms can improve the design space exploration for the synthesis process in terms of time and quality of the result. This paper discusses opportunities and challenges to augment HLS with AI/ML using as example flow the SODA Synthesizer, an open-source hardware generation toolchain which includes SODA-OPT, a hardware/software partitioning and pre-optimization tool developed with the MLIR framework, and PandA-Bambu, a state-of-the art HLS tool. SODA interfaces with OpenROAD to provide a complete end-to-end toolchain.

artificial intelligence↗

Integrated Energy System Investigation for the Eastman Chemical Company, Kingsport, TN Facility

The industrial manufacturing industry is looking to implement new methods of energy production to ensure a consistent energy supply while reducing economic costs and environmental impacts. Much of the manufacturing industry relies on fossil fuels—primarily coal and natural gas—of which there are finite resources subject to price volatility due to an inelastic demand. These resources also come with significant negative environmental impacts related to emissions. While complete independence from fossil fuels is not immediately realistic, options are available to significantly reduce dependency on fossil fuel supplies, including integrated energy systems (IESs) which tightly couple nuclear energy source generators with energy consumers (i.e., industrial factories) to fulfill power and energy requirements. Once realized, optimized IESs may yield significant economic and environmental benefits over traditionally isolated generator and consumer facilities. This report presents a feasibility study for siting an IES to meet the steam and electricity needs of Eastman Chemical Company’s facility in Kingsport, Tennessee. This study explored reactor technology options, evaluation,and optimization,with a focus on meeting the facility’s operational and reliability requirements. This work is part of an ongoing effort by Eastman to be good environmental stewards and meet the demands of their customers by shifting to more environmentally sustainable solutions for their energy needs. Outcomes of this report are also of general interest and value to any design or development team seeking to deploy an IES,as many topics described herein are generally applicable to any nuclear power facility.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Integrated Energy System Investigation for the Eastman Chemical Company, Kingsport, Tennessee Facility

The industrial manufacturing industry is looking to implement new methods of energy production to ensure a consistent energy supply while reducing economic costs and environmental impacts. Much of the manufacturing industry relies on fossil fuels—primarily coal and natural gas—of which there are finite resources subject to price volatility due to an inelastic demand. These resources also come with significant negative environmental impacts related to emissions. While complete independence from fossil fuels is not immediately realistic, options are available to significantly reduce dependency on fossil fuel supplies, including integrated energy systems (IESs) which tightly couple nuclear energy source generators with energy consumers (i.e., industrial factories) to fulfill power and energy requirements. Once realized, optimized IESs may yield significant economic and environmental benefits over traditionally isolated generator and consumer facilities. This report presents a feasibility study for siting an IES to meet the steam and electricity needs of Eastman Chemical Company’s facility in Kingsport, Tennessee. This study explored reactor technology options, evaluation, and optimization, with a focus on meeting the facility’s operational and reliability requirements. This work is part of an ongoing effort by Eastman to be good environmental stewards and meet the demands of their customers by shifting to more environmentally sustainable solutions for their energy needs. Outcomes of this report are also of general interest and value to any design or development team seeking to deploy an IES, as many topics described herein are generally applicable to any nuclear power facility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

RF Accelerator Technology R&D: Report of AF7-rf Topical Group to Snowmass 2021

Accelerator radio frequency (RF) technology has been and remains critical for modern high energy physics (HEP) experiments based on particle accelerators. Tremendous progress in advancing this technology has been achieved over the past decade in several areas highlighted in this report. These achievements and new results expected from continued R&D efforts could pave the way for upgrades of existing facilities, improvements to accelerators already under construction (e.g., PIP-II), well-developed proposals (e.g., ILC, CLIC), and/or enable concepts under development, such as FCC-ee, CEPC, C 3 , HELEN, multi-MW Fermilab Proton Intensity Upgrade, future Muon Colloder, etc. Advances in RF technology have impact beyond HEP on accelerators built for nuclear physics, basic energy sciences, and other areas. Recent examples of such accelerators are European XFEL, LCLS-II and LCLS-II-HE, SHINE, SNS, ESS, FRIB, and EIC. To support and enable new accelerator-based applications and even make some of them feasible, we must continue addressing their challenges via a comprehensive RF R&D program that would advance the existing RF technologies and explore the nascent ones.

43 PARTICLE ACCELERATORS↗

The SMART Cables Initiative for Ocean and Geophysical Observing [Slides]

SMART Cables are becoming a reality, and have the potential to revolutionize submarine oceanographic and geophysical sensing. Pilot / demonstration projects are underway to test the technology and explore the feasibility of incorporating both in-repeater standardized sensor packets but also ancillary sensor types on external, branching nodes. The projects currently in planning will set the standard and influence the norms for the future of SMART systems. The interest of all potential stakeholders and users, and input as to needs and concerns, is welcomed as testing proceeds.

54 ENVIRONMENTAL SCIENCES↗