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At least 1,657 records · Page 92

D-DMTD: Digital Dual Mixer Time Difference

The digital design discussed in the following document is inspired by the digital dual mixer time difference circuit and based on the white paper, Digital femtosecond time difference circuit for CERN's timing system. DMTD is originally an analog technique that measures the time difference between two events with high precision using a commercial time interval counter. Our project applies this analog concept to a digital system programmed onto a Microsemi ProASIC3E FPGA (Field- Programmable Gate Array). D-DMTD is a digital system theoretically capable of measuring the time difference between two digital clock signals with very fine resolution (sub-picosecond) using a relatively low frequency counter. The system essentially acts as a digital phase detector with femtosecond time resolution. The main concern with this processing technique is its feasibility and accuracy when implemented on an FPGA. Another concern is the environmentally-induced, horizontal phase noise in the digital signals; this 'litter" jeopardizes the fidelity of the clocks and generates glitches in the signals. Thus, the majority of the work was focused on determining under what conditions the digital design performs optimally and generates the most accurate estimations for the phase shift.

42 ENGINEERING↗

Guide for Cyber Assessment of Industrial Control Systems Field Devices

Programmable logic controllers (PLCs) and other field devices are important components of many weapons platforms, including vehicles, ships, radar systems, etc. Many have significant cyber vulnerabilities that lead to unacceptable risk. Furthermore, common procedures used during Operational Test and Evaluation (OT&E) may unexpectedly lead to unsafe or severe impacts for the field devices or the underlying physical process. This document describes an assessment methodology that addresses vulnerabilities, mitigations, and safe OT&E.

42 ENGINEERING↗

Performance and Energy Implications for Heterogeneous Computing Systems: A MiniFE Case Study

Heterogeneous computing systems, which employ a mix of general-purpose (GP) processors and accelerators such as graphics processing units (GPUs) or Field Programmable Gate Arrays (FPGAs), have the potential to offer much higher performance and lower energy usage than homogeneous systems. However, designing heterogeneous computing systems to achieve high performance and low energy usage is a challenging task. Designs that offer higher performance do not necessarily lead to lower energy consumption. Furthermore, mapping of applications to different computing devices can play a key role in performance and energy tradeoff. In this report, we present a detailed performance and energy study of executing a specific mini-application on different heterogeneous systems. The results show that hardware choices, application implementations, and mapping of applications to hardware can all significantly impact system performance and energy consumption and that the impact on performance and energy can be quite different. This study forms a basis for modeling the interdependencies of program structures and hardware execution units, which could be used to guide design space exploration.

97 MATHEMATICS AND COMPUTING↗

SST-GPU: An Execution -Driven CUDA Kernel Scheduler and Streaming-Multiprocessor Compute Model

Programmable accelerators have become commonplace in modern computing systems. Advances in programming models and the availability of massive amounts of data have created a space for massively parallel acceleration where the context for thousands of concurrent threads are resident on-chip. These threads are grouped and interleaved on a cycle-by-cycle basis among several massively parallel computing cores. The design of future supercomputers relies on an ability to model the performance of these massively parallel cores at scale. To address the need for a scalable, decentralized GPU model that can model large GPUs, chiplet-based GPUs and multi-node GPUs, this report details the first steps in integrating the open-source, execution driven GPGPU-Sim into the SST framework. The first stage of this project, creates two elements: a kernel scheduler SST element accepts work from SST CPU models and schedules it to an SM-collection element that performs cycle-by-cycle timing using SSTs Mem Hierarchy to model a flexible memory system.

97 MATHEMATICS AND COMPUTING↗

SPE6 Atmospheric Lidar Data User Guide

The Wind Cube v2 is a vertically-profiling, remote sensing instrument based on pulsed Light Detection and Ranging (Lidar) technology that provideshigh quality wind measurements on par with an IEC calibrated meteorological mast. The instrument uses four radial laser beams (0, 90, 180, 270° in the azimuth, scan angle 28° from zenith) and one vertically (V) orientated beam to measure flow characteristics from 40 m up to 290 m above ground level at 12 user-programmable heights (Figure 1). Lidar creates a “virtual” meteorological tower whereby the characteristics of the wind in the lower part of the planetary boundary layer are sampled. It takes roughly 4 seconds to complete a full conical scan, followed by the 5thbeam (V) pointed in the vertical position. The underlying principle of pulsed lidar measurements of wind is the use of optical heterodyne (coherent) detection, in which laser pulses are transmitted into the atmosphere and scattered off of naturally-occurring small dust particles or aerosols entrained in the ambient flow field (Figure 2). Radial velocity is proportional to Doppler frequency shift. In simple to moderately complex terrain wind speed accuracy is 0.1 m/s, wind direction accuracy is 1.5°.

58 GEOSCIENCES↗

Light Material Interactions in Energy Conversion (Final Report)

The scientific vision of the “Light-Material Interactions in Energy Conversion” Energy Frontier Research Center (LMI-EFRC) is embodied in our mission statement: ‘to tailor the morphology, complex dielectric structure, and electronic properties of matter so as to sculpt the flow of sunlight and heat, enabling light conversion to electrical energy with unprecedented efficiency’. Founded in 2009, the LMI-EFRC has become a national resource for fundamental optical principles and phenomena relevant to solar energy conversion, addressing new scientific opportunities that enable efficient utilization of the entire visible and infrared solar resource. The LMI-EFRC is directed by Prof. Ralph Nuzzo and centered at its lead institution, the California Institute of Technology. The Center is an integrated and collaborative partnership of research leaders in photonics and photonic materials, comprising 14 faculty investigators that span six academic departments at five institutions, including Profs. Harry Atwater, Andrei Faraon, Nathan Lewis, and Austin Minnich at Caltech; Profs. Ralph Nuzzo, Paul Braun and John Rogers at the University of Illinois at Urbana-Champaign; Prof. Jennifer Lewis at Harvard University; Profs. Mark Brongersma, Jennifer Dionne, and Shanhui Fan at Stanford University; and Profs. Paul Alivisatos, Eli Yablonovitch, and Xiang Zhang at Lawrence Berkeley National Laboratory. The Center is organized into four research groups (RGs) that address scientific themes related to light-matter interactions, with each team spanning multiple institutional partners and designed to meet our scientific objectives. Notable project outcomes that address the LMI Mission and 2014-2018 goals include: (1) RG1 “New Light Management Mechanisms” demonstrated tunable and active nanostructured patterned surfaces (‘metasurfaces’) for control of light absorption, reflection, and propagation. (2) RG2 “Solar Spectrum Control and Conversion” developed colloidal nanocrystals with designer optical properties for fundamental studies of solar spectrum control and conversion. (3) RG3 “Thermal Photon Harvesting” established photonic design principles to harness and control thermal photons in novel conversion systems. (4) RG4 “Programmable Assembly of Photonic and Electronic Architectures” developed powerful new methods for light- and matter-based additive fabrication of electronic and photonic architectures.

14 SOLAR ENERGY↗

Comparative Assessment of Experimental Testing of Instrument with an Embedded Digital Device Using Model-Based and Conventional Methods

The use of digital equipment has not been widespread in U.S. nuclear facilities. A major contributing factor to this situation arises from regulatory concerns about common cause failures (CCFs) stemming from the use of identical software in redundant systems, questions as to how to quantify the reliability of software-based products, validity of tools that are used for software verification and validation (V&V), and the effectiveness of software QA procedures. Compounding the concerns are sporadic incidents of digital equipment malfunctions in nuclear power plants, including lockups resulting from software memory leaks, feedwater control malfunctions due to excessive traffic on Ethernet networks, software logic errors, and other problems leading to plant trips. Additionally, the limited amount of demonstrated research and a lack of industry consensus on quantitative software reliability methodologies has hindered the widespread adoption of digital I&C in the nuclear industry. In a recent Regulatory Issue Summary (RIS), the U.S. Nuclear Regulatory Commission (NRC) identified concerns about the impact of greater use of instrumentation and control (I&C) equipment with an embedded digital device (EDD) [1]. Specifically, the NRC staff states that increased use of such devices “may increase a facility’s vulnerability to a CCF” (i.e., common-cause failure). The prevailing NRC guidance regarding software CCF (SCCF) identifies two design attributes that are acceptable for eliminating CCF concerns: (1) diversity or (2) testability (specifically, 100% testability). Either solution can result in high costs and remaining licensing uncertainty (i.e., how much diversity is enough? how to ensure test coverage of every possible sequence of device states?). Consequently, many utilities and reactor designers have limited or avoided more extensive use of digital technology to minimize licensing, scheduling, and financial risk. Without development of cost effective qualification methods to satisfy regulatory requirements and address the potential for CCF vulnerability associated with EDDs, the nuclear power industry may not be able to realize the benefits of digital technology achieved by other industries. In order to address these challenges, the U.S. Department of Energy (DOE) is sponsoring this research to assess the prospect of CCF in digital I&C equipment. The purpose of the current research is to develop an effective approach employing science-based methods to resolve concerns about CCF vulnerability that serve to inhibit deployment of advanced instrumentation (e.g., sensors, actuators, microcontrollers) with EDDs in nuclear power applications. The research objectives address the challenge of establishing high levels of safety and reliability assurance needed for the qualification of EDDs (e.g., microprocessors, programmable logic devices) that are subject to software design faults, complex failure modes, and CCF vulnerability. Specific objectives are: (1) assess the regulatory context for treatment of CCF vulnerability a graded approach to their qualification, (3) develop and extend model-based testing methods to enable effective demonstration of whether devices are subject to CCF, which may arise from vulnerabilities introduced at any stage of the design lifecycle, (4) establish a cost-effective testing framework that incorporates automation and test scenario prioritization, and (5) demonstrate the qualification approach through selection and testing of candidate digital device(s). This report documents an assessment of the results from experimental testing of a representative instrument with an embedded digital device. The experiment serves as a proof-of-concept demonstration of a model-based testing (MBT) framework. The objective of MBT is to ensure that an EDD undergoes suitably comprehensive testing to establish that it is not subject to SCCF. The approach by which MBT accomplishes this objective is through development and application of an effective test suite that provides the appropriate coverage to detect the full range of postulated faults that may arise at the requirements, design, and code (implementation) level of the EDD software. The findings of the experiment involve the application of the MBT framework by Ohio State University (OSU) through testing of the selected demonstration instrument (i.e., the prototype smart pressure sensor developed by Virginia Commonwealth University, VCU). In addition, the experiment findings also involve application of a more conventional black-box testing approach that serves as a baseline against which the MBT methodology can be compared. The primary outcome documented in this report is the comparative analysis of the capabilities demonstrated for each method. The results of the analysis demonstrate clear benefits that arise from the MBT methodology. The comparison indicates greater effectiveness from the more comprehensive evidence available through MBT and enhanced efficiency achieved through automation within the MBT framework. The structure of the report addresses the approach and application of each test method as well as the comparative analysis of the experimental results. Chapter 2 gives a summary overview of the demonstration approach. Chapter 3 covers the baseline testing and Chapter 4 documents the model-based testing. Chapter 5 describes the findings of the comparative analysis and presents the conclusions that can be drawn about the effectiveness and efficiency of the MBT methodology.

47 OTHER INSTRUMENTATION↗

Solar Resource Calibration, Measurement, and Dissemination: Final Report FY 2016-FY 2018

The Solar Resource Calibration, Measurement, and Dissemination project supports the U.S. Department of Energy's Solar Energy Technologies Office (SETO) initiative to make solar energy cost-competitive with other forms of electricity by improving the tools and methods to measure and model solar radiation and therefore reduce uncertainty in predicting solar output and improve the bankability of solar projects. This project has three tasks that conduct research on advancing solar resource measurements and modeling: Task 1: Applied solar Radiation Measurements. Task 2: National Solar Radiation Data Base (NSRDB). Task 3: Knowledge Sharing. The National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) activities ensure traceable solar measurements throughout the United States that are essential for project feasibility, due diligence, financing, and plant operations. The SRRL houses NREL's Baseline Measurement System (BMS), which provides a platform for improving the accuracy of solar measurements through research to improve the calibration and characterization of instruments and enable the development of new measurement technology and standards. The platform contains a variety of instruments measuring solar radiation and other meteorological parameters. Following best practices, BMS instruments are calibrated to ensure traceability to the World Radiometric Reference in compliance with ISO/IEC 17025 accreditation requirements. The BMS data sets are quality-controlled and made publicly available through the Measurement and Instrumentation Data Center website. The NSRDB is the most accessed public database of solar irradiance and associated weather parameters for use in energy modeling. It supports SETO's goals of reducing barriers to high penetrations of solar technologies by providing easy access to high-quality, foundational data essential for innovative product development and downstream modeling through the NSRDB website. Data are currently available for the contiguous United States and beyond for 20 years covering 1998-2017. The Physical Solar Model (PSM) that underpins the current NSRDB data sets is a unique physics-based model that has been developed at NREL and has opened the door to the use of next-generation satellite data sets for solar resource assessment and forecasting. Through the American Society for Testing Materials (ASTM) International and other international standards organizations, NREL continues to provide leadership in the development of standards that are relevant to the measurement and modeling of solar radiation for solar energy applications. Standards developed cover the calibration method of pyrheliometers (direct normal irradiance measurements), pyranometers (global horizontal irradiance measurements), spectroradiometers, ultraviolet radiometers, correct field deployment of these instruments, spectral distribution reference tables for photovoltaic modeling, and transfer of indoor calibrations. Further, NREL leads the International Energy Agency (IEA) Photovoltaic Power Systems Programme Task 16: Subtask 1, which focuses on the evaluation of current and emerging resource assessment methodologies. NREL and the IEA updated the Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications, which is widely used by the solar industry.

14 SOLAR ENERGY↗

Fabrication and Mechanical Testing of Block Shear Joints to Measure Ultimate Shear Strength in Adhesive-Bonded High Explosive (HE) Joints (Progress Summary)

Small-scale adhesive-bonded HE joints were designed, using roughly 4% of the HE mass required by fixtures described in the ASTM D905 standard. Custom 3D-printed bonding fixtures were designed, fabricated, and used to generate reproducible joints with programmable bondline thickness. A custom 3D-printed block shear testing fixture was designed, fabricated, and employed to measure the shear strength of test joints.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

IEA Wind TCP Task 26–Wind Technology, Cost, and Performance Trends in Denmark, Germany, Ireland, Norway, Sweden, the European Union, and the United States: 2008-2016

The International Energy Agency Wind Technology Collaboration Programme (IEA Wind TCP) Task 26 - The Cost of Wind Energy represents an international collaboration dedicated to exploring the past, present, and future cost of wind energy. The countries that are currently represented by participating organizations in IEA Wind TCP Task 26 included in this report are Denmark, Germany, Ireland, Norway, Sweden, the European Union, and the United States. This report discusses trends from 2008 through 2016 that affected the cost of land-based wind energy in each country. The cost of wind energy during this period is compared with the market value of wind energy in the respective electricity market for each country. This report builds from previous analysis conducted since the inception of Task 26 in 2009. Schwabe et al. (2011) explored differences in the cost of wind energy in 2008 among countries participating in Task 26 at that time. Vitina et al. (2015) presented turbine- and project-level trends in the wind industry from 2008 to 2012, including wind project size, turbine size, specific power and hub height, project performance, investment costs, operation and maintenance (O&M) costs, and project financing. These inputs are used to calculate the levelized cost of energy (LCOE), a widely recognized metric for understanding how technology performance, capital investment, operations, and financing impact the life cycle cost of building and operating a wind project. Both prior reports - as well as this report - used this metric to estimate the cost of wind energy.

17 WIND ENERGY↗

Sierra/SD - Theory Manual

Sierra/SD provides a massively parallel implementation of structural dynamics finite element analysis, required for high fidelity, validated models used in modal, vibration, static and shock analysis of structural systems. This manual describes the theory behind many of the constructs in Sierra/SD. For a more detailed description of how to use Sierra/SD , we refer the reader to Sierra/SD, User's Notes . Many of the constructs in Sierra/SD are pulled directly from published material. Where possible, these materials are referenced herein. However, certain functions in Sierra/SD are specific to our implementation. We try to be far more complete in those areas. The theory manual was developed from several sources including general notes, a programmer_notes manual, the user's notes and of course the material in the open literature.

97 MATHEMATICS AND COMPUTING↗

Balar: A SST GPU Component for Performance Modeling and Profiling

Programmable accelerators have become commonplace in modern computing systems. Advances in programming models and the availability of massive amounts of data have created a space for massively parallel accelerators capable of maintaining context for thousands of concurrent threads resident on-chip. These threads are grouped and interleaved on a cycle-by-cycle basis among several massively parallel computing cores. One path for the design of future supercomputers relies on an ability to model the performance of these massively parallel cores at scale. The SST framework has been proven to scale up to run simulations containing tens of thousands of nodes. A previous report described the initial integration of the open-source, execution-driven GPU simulator, GPGPU-Sim, into the SST framework. This report discusses the results of the integration and how to use the new GPU component in SST. It also provides examples of what it can be used to analyze and a correlation study showing how closely the execution matches that of a Nvidia V100 GPU when running kernels and mini-apps.

97 MATHEMATICS AND COMPUTING↗

SIERRA/Aero User Manual (V. 4.40)

SIERRA/Aero is a compressible fluid dynamics program intended to solve a wide variety compressible fluid flows including transonic and hypersonic problems. This document describes the commands for assembling a fluid model for analysis with this module, henceforth referred to simply as Aero for brevity. Aero is an application developed using the SIERRA Toolkit (STK). The intent of STK is to provide a set of tools for handling common tasks that programmers encounter when developing a code for numerical simulation. For example, components of STK provide field allocation and management, and parallel input/output of field and mesh data. These services also allow the development of coupled mechanics analysis software for a massively parallel computing environment. In the definitions of the commands that follow, the term Real_Max denotes the largest floating point value that can be represented on a given computer. Int_Max is the largest such integer value.

42 ENGINEERING↗

Water Footprint of European Rooftop Photovoltaic Electricity based on Regionalised Life Cycle Inventories

The water use of photovoltaic (PV) electricity has been investigated in very few studies so far, which may be due to the low water demand of PV systems during operation. In this study, the water consumption and water withdrawal of electricity generated by PV systems were assessed by considering all life cycle stages and by taking account of country-level regional differences in water availability. The life cycle inventories of the manufacture of monocrystalline silicon (mono-Si) and cadmium telluride (CdTe) PV modules are based on data collected between 2010 and 2013 and take account of the shares of different countries in total global production. The water use in the life cycle inventories of European rooftop PV systems and conventional electricity generation technologies was regionalised to the country or region (such as continents, political or geographic entities of several countries) level and complemented by the share of water lost by evaporation. The AWARE (Available WAter REmaining) method was used to assess the water stress impact caused by water consumption and water withdrawal of electricity generation by European rooftop PV systems as well as by reservoir hydroelectric power plants and large-scale hard coal and nuclear power plants in Europe. The functional unit of this analysis is 1 kWh of alternating current (AC) electricity (at busbar). The life cycle inventories were linked to KBOB (Coordination Group for Construction and Property Services) life cycle inventory data DQRv2:2016, which are based on ecoinvent data v2.2 and contain updated life cycle inventory data in relevant economic sectors. This study was financed by the Swiss Federal Office of Energy (SFOE) and carried out in the framework of the Task 12 of the Photovoltaic Power Systems Programme (PVPS) of the International Energy Agency (IEA).

14 SOLAR ENERGY↗

Life Cycle Inventory of Current Photovoltaic Module Recycling Processes in Europe

With the rapid and accelerating growth of PV module installation and an increase of PV modules from the nineteen eighties and nineties reaching the end of their 30 year lifespan, their proper end of life treatment gets into focus. This report deals with the approaches, the environmental impacts and the recovered materials of PV module recycling. In this report, the environmental life cycle assessment of the current generation recycling of crystalline silicon (c-Si) and cadmium telluride (CdTe) PV modules is described. Due to the still limited waste stream today, c-Si PV modules are mainly treated in recycling plants designed for treatment of laminated glass, metals or electronic waste. Only the bulk materials glass, aluminium and copper are recovered, while the cells and other materials such as plastics are incinerated. CdTe PV modules have been treated in dedicated recycling plants for many years and life cycle inventories of this process have been published. The semiconductor is recovered in addition to glass and copper. Life cycle inventories of the recycling of current c-Si and CdTe PV modules are compiled following two modelling approaches related to recycling. The cut-off approach uses economic allocation to divide the total efforts of the recycling process between the treatment of the used PV module and the recovered products. The end-of-life approach considers the recycling process separately from the potentially avoided burdens due to recovered materials. The life cycle inventories of c-Si PV module recycling are based on data obtained from four European recyclers surveyed between 2015 and 2016. For CdTe PV module recycling, the life cycle inventories were established based on published data for the First Solar recycling facility in Germany. The life cycle impact assessment is done based on six environmental indicators previously identified as most relevant for PV electricity: particulate matter, freshwater ecotoxicity, human toxicity non-cancer effects, human toxicity cancer effects, mineral, fossil and renewable resource depletion and climate change. The life cycle inventories according to the cut-off approach can be applied to complement existing life cycle inventory data on PV systems. The environmental impacts of the recycling of c-Si PV modules are very small (maximum 1.1 %) compared to the impacts caused by the production of a 3 kWp residential PV system mounted on a slanted roof. In the case of CdTe PV module recycling, the treatment of the PV panels has the highest but still rather minor contribution in the indicator climate change (4.8 %). The life cycle inventories according to the end-of-life approach allow an assessment of the net environmental benefits of recycling. The recovery of glass, metals, and semiconductor material from c-Si and CdTe PV modules causes lower environmental impacts than the extraction, refinement and supply of the respective materials from primary resources. The highest potential benefits are observed in the indicator mineral, fossil and renewable resource depletion. The data quality of the recycling of c-Si PV modules is classified as fair since only limited information is available. In contrast, the data quality of CdTe PV module recycling is considered very good. The study was financed by the Swiss Federal Office of Energy (SFOE) and carried out in the framework of the Task 12 of the Photovoltaic Powers System Programme (PVPS) of the International Energy Agency (IEA).

14 SOLAR ENERGY↗

End-of-Life Management of Photovoltaic Panels: Trends in PV Module Recycling Technologies

Photovoltaic (PV) technology is one of the most promising technologies for improving energy security and mitigating climate change. The PV market is growing rapidly, and further market expansion is expected all over the world. In addition to its positive impacts on energy security and climate change, PV technology is also among the most environmentally friendly technologies of all energy and electricity generation technologies, particularly when evaluated from a life-cycle viewpoint, including end-of-life management. This means that proper end-of-life management is an indispensable issue for 'clean' energy technologies. All technologies eventually degrade to where they enter their end-of-life stage, eventually requiring replacement. PV modules have a useful lifespan of approximately 30 years. With PV deployment increasing exponentially, the number of PV modules that reach the end of useful life will also greatly increase after the time lag of operation, accumulating proportionately as waste. A report published by International Energy Agency Photovoltaic Power Systems Programme (IEA PVPS) Task12 and the International Renewable Energy Agency (IRENA) in 2016 projected waste PV modules globally to amount to 1,7-8,0 million tons cumulatively by 2030 and to 60-78 million tons cumulatively by 2050. Generally, sustainable waste management offers opportunities known as the 3Rs: reduce, reuse, and recycle. When a product cannot be repaired or reused, recycling is the next preferable option before disposing as waste. In anticipation of the large volume of waste PV modules, and to retain PV's position as a clean energy technology, PV module recycling has become an important emerging topic, and various discussions and activities have been conducted and developed by governments, organizations, and companies. (Discussions on the topic of PV module reuse are considered to be less mature.) The EU Waste Electrical and Electronic Equipment (WEEE) Directive revised in 2012 (2012/19/EU) addresses the waste management of all electronics, including waste PV modules, in the EU member states. It requires 75%/65% (recovery/recycling rate) of waste PV modules by mass to be recycled through 2016, then increases to 80%/75% through 2018 and to 85%/80% thereafter. In addition to such a regulatory scheme, it is obvious that recycling technologies must be available to meet the increasing requirements of WEEE. Available recycling facilities that treat PV modules can meet current WEEE requirements; additional research and development (R&D) is required to meet subsequent WEEE requirements at reasonable cost. This report aims to provide an international survey of trends related to the development of PV module recycling technology from the perspective of both the private and public sectors. For the private sector, we review patents, as patent filing has been increasing since 2011. For the public sector, we review R&D plans and investments made by many countries active in PV module recycling technology development. Because it takes a long time to develop and commercialize new technologies, we hope that this report will accelerate technology development through transparent sharing of status and insight pertaining to the development of PV module recycling technologies. Managing end-of-life PV modules to recover valuable materials that can displace virgin ones is an important step toward meeting the challenge of sustainabiliy.

14 SOLAR ENERGY↗

End of Life Management: Solar Photovoltaic Panels

Technical potential of materials recovered from end-of-life solar PV panels could exceed $15 billion by 2050. The global solar photovoltaic (PV) boom currently underway will represent a significant untapped business opportunity as decommissioned solar panels enter the waste stream in the years ahead, according to a report released today by the International Renewable Energy Agency (IRENA) and the International Energy Agency's Photovoltaic Power Systems Programme (IEA-PVPS). The report, End-of-Life Management: Solar Photovoltaic Panels, is the first-ever projection of PV panel waste volumes to 2050 and highlights that recycling or repurposing solar PV panels at the end of their roughly 30-year lifetime can unlock a large stock of raw materials and other valuable components. It estimates that PV panel waste, comprised mostly of glass, could total 78 million tonnes globally by 2050. If fully injected back into the economy, the value of the recovered material could exceed USD 15 billion by 2050. This potential material influx could produce 2 billion new panels or be sold into global commodity markets, thus increasing the security of future PV supply or other raw material-dependent products. The report suggests that addressing growing solar PV waste, and spurring the establishment of an industry to handle it, would require: the adoption of effective, PV-specific waste regulation; the expansion of existing waste management infrastructure to include end-of-life treatment of PV panels, and; the promotion of ongoing innovation in panel waste management. In most countries, PV panels fall under the classification of 'general waste' but the European Union (EU) was the first to adopt PV-specific waste regulations, which include PV-specific collection, recovery, and recycling targets. EU's directive requires all panel producers that supply PV panels to the EU market (wherever they may be based) to finance the costs of collecting and recycling end-of-life PV panels put on the market in Europe. End-of-Life Management: Solar Photovoltaic Panels, is the second of several solar-focused publications IRENA is releasing this summer. Last week, IRENA released The Power to Change, which predicts average costs for electricity generated by solar and wind technologies could decrease by between 26 and 59 per cent by 2025. Later this week, IRENA will release Letting in the Light: How Solar Photovoltaics Will Revolutionize the Electricity System - which provides a comprehensive overview of solar PV across the globe and its prospects for the future.

14 SOLAR ENERGY↗

Dynamical System for Resilient Computing

The effort to develop larger-scale computing systems introduces a set of related challenges: Large machines are more difficult to synchronize. The sheer quantity of hardware introduces more opportunities for errors. New approaches to hardware, such as low-energy or neuromorphic devices are not directly programmable by traditional methods.

97 MATHEMATICS AND COMPUTING↗