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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Wind power forecasting: IEA Wind Task 36 & future research issues

Here, this paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.

17 WIND ENERGY↗

Forecasting for the Weather Driven Energy System - A New Task under IEA Wind

The energy system needs a range of forecast types for its operation in addition to the narrow wind power forecast that has been the focus of considerable recent attention. Therefore, the group behind the former IEA Wind Task 36 Forecasting for Wind Energy has initiated a new IEA Wind Task with a much broader perspective, which includes prospective interaction with other IEA Technology Collaboration Programmes such as the ones for PV, hydropower, system integration, hydrogen etc. In the new IEA Wind Task 51 (entitled "Foreacsting for the Weather Drive Energy System") the existing Work Packages (WPs) are complemented by work streams in a matrix structure. The Task is divided in three WPs according to the stakeholders: WP1 is mainly aimed at meteorologists, providing the weather forecast basis for the power forecasts. In WP2, the forecast service vendors are the main stakeholders, while the end users populate WP3. The new Task 51 started in January 2022. Planned activities include 4 workshops. The first will focus on the state of the art in forecasting for the energy system plus related research issues and be held during September 2022 in Dublin. The other three workshops will be held later during the 4-year Task period and address (1) seasonal forecasting with emphasis on Dunkelflaute, storage and hydro, (2) minute-scale forecasting, and (3) extreme power system events. The issues and conclusions of each of the workshops will be documented by a published paper. Additionally, the Recommended Practice on Forecast Solution Selection will be updated to reflect the broader perspective.

geophysics computing↗

Evaluating the Nation's Pipeline Infrastructure with NETL's Advanced Infrastructure Integrity Model (AIIM)

This poster is a part of BIL-EDX4CCS Task 36: Advanced Infrastructure Integrity Modeling to Evaluate Existing Energy Infrastructure Reusability and Risk, the goal of which is to produce a smart tool that will assess existing energy infrastructure reusability and risk using the Advanced Infrastructure Integrity Model (AIIM). This model forecasts lifespan and potential risk using a multitude of factors such as incidents reports, structural characteristics, and the surrounding environment. The project aims to provide scientific insights for a better understanding of carbon storage (CS), potential to support CS stakeholder needs, national decarbonization, and mitigating climate change. AIIM will utilize an energy infrastructure database as its input, developed by acquiring publicly available data as well as NETL derived products. These resources include incidents, geohazards, and infrastructure variables. Soil data in the form of rasters and pipeline incident reports were processed and a script was developed to count the number of times features such as roads, railroads, and rivers intersected with pipeline segments which were then converted to points. Distance to oil and natural gas wells, petroleum ports, intermodal freight facilities, and geologic structures were also calculated. After data preparation and quality control was completed, the data was integrated into the pipeline points. Once models are complete, a smart tool will be created in the form of an online dashboard.

Malay, Caleb↗

An OpenMP GPU-offload implementation of a non-equilibrium solidification cellular automata model for additive manufacturing

Here, in this paper, performance strategies on GPU-based HPC platforms of a cellular automata (CA) simulation code for non-equilibrium solidification, including nucleation, grain growth, solute partitioning and transport for the metal additive manufacturing (AM) process are investigated using OpenMP 4.5. To accurately report the speed-up for multicore CPUs and GPUs, a rigorous performance analysis employed optimizations appropriate for both CPU-only code (baseline) and GPU offload codes for an isothermal test problem. The performance results on Summit at the Oak Ridge Leadership Computing Facility indicate that using a precomputed list of interface cells significantly decreased the wall-clock time on GPUs. The speedup due to GPU acceleration was evaluated for a full Summit node and measured to be 1.8X when comparing a 6 MPI tasks run with 6 GPUs versus 36 MPI tasks on the CPU only. That speed-up was found to be 7.9X when comparing 6 MPI tasks with 6 GPUs versus the 6 MPI tasks running on the CPU only. Performance measurements showed that system total time is almost constant for runs with more than 96 MPI tasks (or GPUs), indicating that the GPU-accelerated code showed an excellent weak scaling performance. Finally, a rapid directional solidification problem was considered to demonstrate the CA code capability on Summit. It was found that a mesh size of at least 0.05 μm is recommended for the AM-like simulations in order to obtain accurate elongated grain microstructure and elongated subgrain features, which are in qualitative good agreement with experimental data. The results presented in this study indicate that the performance strategies on GPU-based HPC platforms for the CA code are appropriate for novel HPC exascale platforms.

36 MATERIALS SCIENCE↗

TU-F-CAMPUS-T-04: An Evaluation of Out-Of-Field Doses for Electron Beams From Modern Varian and Elekta Linear Accelerators

Purpose: Accurately determining out-of-field doses when using electron beam radiotherapy is of importance when treating pregnant patients or patients with implanted electronic devices. Scattered doses outside of the applicator field in electron beams have not been broadly investigated, especially since manufacturers have taken different approaches in applicator designs. Methods: In this study, doses outside of the applicator field were measured for electron beams produced by a 10×10 applicator on two Varian 21iXs operating at 6, 9, 12, 16, and 20 MeV, a Varian TrueBeam operating at 6, 9, 12, 16, and 20 MeV, and an Elekta Versa HD operating at 6, 9, 12 and 15 MeV. Peripheral dose profiles and percent depth doses were measured in a Wellhofer water phantom at 100 cm SSD with a Farmer ion chamber. Doses were compared to peripheral photon doses from AAPM’s Task Group #36 report. Results: Doses were highest for the highest electron energies. Doses typically decreased with increasing distance from the field edge but showed substantial increases over some distance ranges. Substantial dose differences were observed between different accelerators; the Elekta accelerator had much higher doses than any Varian unit examined. Surprisingly, doses were often similar to, and could be much higher than, doses from photon therapy. Doses decreased sharply with depth before becoming nearly constant; the dose was found to decrease to a depth of approximately E(MeV)/4 in cm. Conclusion: The results of this study indicate that proper shielding may be very important when utilizing electron beams, particularly on a Versa HD, while treating pregnant patients or those with implanted electronic devices. Applying a water equivalent bolus of Emax(MeV)/4 thickness (cm) on the patient would reduce fetal dose drastically for all clinical energies and is a practical solution to manage the potentially high peripheral doses seen from modern electron beams. Funding from NIH Grant number: #CA180803.

60 APPLIED LIFE SCIENCES↗

SU-E-T-559: Monte Carlo Simulation of Cobalt-60 Teletherapy Unit Modeling In-Field and Out-Of-Field Doses for Applications in Computational Radiation Dosimetry

Purpose: Mean organ doses from structures located in field and outside of field boundaries during radiotherapy treatment must be considered when looking at secondary effects. Treatment planning in patients with 40 years of follow-up does not include 3-D treatment planning images and did not estimate dose to structures out of the direct field. Therefore, it is of interest to correlate actual clinical events with doses received. Methods: Accurate models of radiotherapy machines combined with whole body computational phantoms using Monte Carlo methods allow for dose reconstructions intended for studies on late radiation effects. The Theratron-780 radiotherapy unit and anatomically realistic hybrid computational phantoms are modeled in the Monte Carlo radiation transport code MCNPX. The major components of the machine including the source capsule, lead in the unit-head, collimators (fixed/adjustable), and trimmer bars are simulated. The MCNPX transport code is used to compare calculated values in a water phantom with published data from BJR suppl. 25 for in-field doses and experimental data from AAPM Task Group No. 36 for out-of-field doses. Next, the validated cobalt-60 teletherapy model is combined with the UF/NCI Family of Reference Hybrid Computational Phantoms as a methodology for estimating organ doses. Results: The model of Theratron-780 has shown to be agree with percentage depth dose data within approximately 1% and for out of field doses the machine is shown to agree within 8.8%. Organ doses are reported for reference hybrid phantoms. Conclusion: Combining the UF/NCI Family of Reference Hybrid Computational Phantoms along with a validated model of the Theratron-780 allows for organ dose estimates of both in-field and out-of-field organs. By changing field size, position, and adding patient-specific blocking more complicated treatment set-ups can be recreated for patients treated historically, particularly those who lack both 2D/3D image sets.

61 RADIATION PROTECTION AND DOSIMETRY↗

Broadly Applicable Dose Model for Radiotherapy Beams from 6-25 MV

The goal of modern external beam radiotherapy is to deliver a highly targeted radiation dose to a specified treatment volume while sparing the healthy surrounding tissue as much as possible. However, some healthy tissue radiation exposure is unavoidable. Healthy tissue in the margin of the treatment field will receive absorbed doses on the order of the prescribed dose, and tissue far out of field will receive stray dose from scattered and leakage radiation. These doses can lead to late effects such as secondary cancers both near the treatment field and far out of field in tissues only receiving stray radiation dose. Many researchers have investigated algorithms to model absorbed dose from external beam photon radiation therapy; however, none of these works have fully addressed the stray dose far from the treatment field. The AAPM Task Group Report No. 36 described three main sources of stray radiation from external beam radiation therapy delivered with electron linear accelerators. Radiation scattered from the treatment head, known as head scatter, is primarily important within about 10 cm from the field edge. Patient scatter is an important source up to around 30 cm from the field edge. Finally, leakage radiation emanates from the treatment enclosure and predominates the stray radiation dose beyond about 30 cm. Monte Carlo simulations have been a useful research tool for modeling stray dose, but these methods have not found use in clinical settings due to their complexity and long computational times. The feasibility of analytical models to predict stray dose from radiation therapy has been supported by several works, but few attempts have been made at developing models accurate for both in-field and out-of-field doses. Jagetic and Newhauser reported on one such model that predicts absorbed dose from therapeutic, scatter, and leakage radiation with promising results. This model was validated at 6 MV for Conformal Radiation Therapy (CRT) beams from an Elekta linac. Intensity Modulated Radiation Therapy (IMRT) was not considered, and the model has not been tested at beam energies greater than 6 MV. Additionally, this model relies on proprietary, machine specific parameters, and so adapting the model for use on treatment units from other manufacturers is not straightforward. In this study we aim to test whether a physics-based analytical modeling approach is broadly applicable and if sufficient accuracy can be achieved without the need for proprietary, machine specific parameters. In order to accomplish this, a new analytical model was developed that does not rely on machine specific parameters, so that it can easily be trained on measurements from whatever treatment machine is available at a given clinic. This model was tested using measured data from a variety of treatment machines and techniques in the 6 MV to 25 MV energy interval. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Microbial Curing of Cement for Energy Applications

Rutgers University, Lawrence Livermore National Laboratory, and the University of Arizona executed this program over 36 months with a 4-Task Program: (M1)-Microbial Engineering (M2)-Microstructure Modelling, (M3) Cement and Concrete Formulation, (M4)-Techno-economic analysis (TEA) and lifecycle assessment (LCA). This program developed a new carbonate cement concrete manufacturing process called microbial curing (MBC). MBC utilizes in-situ microbial production of CO 2 that dissolves into pore-bound water to carbonate a cementitious material creating a bonding matrix of CaCO 3 and SiO 2 that hardens and densifies the material. This is the first work of this type where calcium silicate was used in microbial studies. All other work reported in the literature always used a soluble form of calcium. This final report describes the work done in the final quarter, the best procedures and results, and the final techno-economic and lifecycle analyses. This quarter, we cast and cured twenty-five (4”x8”) cylinder samples. The compressive strength, split tensile, Young’s modulus, chloride permeability, and creep measurements were performed. These measurements demonstrated that MBC of calcium silicate concrete exhibits scaling problems due to the escape of ammonia gas, a product of the microbial reaction to generate CO 2 . As curing proceeds, the ability for the gas to escape from within the cylinder is restricted by the outer cylindrical portions densifying, making the outer portion highly impermeable to gas flow. In contrast, the small samples cured are uniformly cured, forming materials whose mechanical properties are 7x better than the large samples. This problem needs to be solved before this technology can be commercialized. The techno-economic and lifecycle analyses indicate that the technology developed in this program exhibits a significant opportunity to reduce the cost of cement and CO 2 emissions associated with concrete, provided the curing issue associated with larger samples can be addressed.

36 MATERIALS SCIENCE↗

SU-F-T-305: Clinical Effects of Dosimetric Leaf Gap (DLG) Values Between Matched Varian Truebeam (TB) Linacs

Purpose: The dosimetric leaf gap (DLG) is an important parameter to be measured for dynamic beam delivery of modern linacs, like the Varian Truebeam (TB). The clinical effects of DLG-values on IMRT and/or VMAT commissioning of two “matched” TB linacs will be presented.Methods and Materials: The DLG values on two TB linacs were measured for all energy modalities (filtered and FFF-modes) as part of the dynamic delivery mode commissioning (IMRT and/or VMAT. After the standard beam data was modeled in eclipse treatment planning system (TPS) and validated, IMRT validation was performed based on TG1191 benchmark, IROC Head-Neck (H&N) phantom and sample of clinical cases, all measured on both linacs. Although there was a single-set of data entered in the TPS, a noticeable difference was observed for the DLG-values between the linacs. The TG119, IROC phantom and selected patient plans were furnished with DLG-values of TB1 for both linacs and the delivery was performed on both TB linacs for comparison. Results: The DLG values of TB1 was first used for both linacs to perform the testing comparisons. The QA comparison of TG119 plans revealed a great dependence of the results to the DLG-values used for the linac for all energy modalities studied, especially when moving from 3%/3mm to 2%/2mm γ-analysis. Conclusion: The DLG-values have a definite influence on the dynamic dose, delivery that increases with the plan complexity. We recommend that the measured DLG-values are assigned to each of the “matched” linacs, even if a single set of beam data describes multiple linacs. The user should perform a detail test of the dynamic delivery of each linac based on end-to-end benchmark suites like TG119 and IROC phantoms.1Ezzel G., et al., “IMRT commissioning: Multiple institution planning and dosimetry comparisons, a report from AAPM Task Group 119.” Med. Phys. 36:5359–5373 (2009). partly supported by CAMC Cancer Center and Alliance Oncology.

60 APPLIED LIFE SCIENCES↗

Program Fuzzing on High Performance Computing Resources

American Fuzzy Lop (AFL) is an evolutionary fuzzer that is strategically implemented as a tool for discovering bugs in software during vulnerability research. This work seeks to understand how to best implement AFL on the High-Performance Computing resources available on the unclassified network at Sandia National Laboratories. We investigate various methods of executing AFL, requesting varying numbers of tasks on single compute nodes with 36 physical cores and 72 total threads. A Python script called Blue Claw is presented as an automated testbed generator tool to assist in the tedious process of creating and executing experiments of any scale and duration.

97 MATHEMATICS AND COMPUTING↗

Modeling a Million-Node Slim Fly Network Using Parallel Discrete-Event Simulation

As supercomputers close in on exascale performance, the increased number of processors and processing power translates to an increased demand on the underlying network interconnect. The Slim Fly network topology, a new lowdiameter and low-latency interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this paper, we present a high-fidelity Slim Fly it-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate our Slim Fly model with the Kathareios et al. Slim Fly model results provided at moderately sized network scales. We further scale the model size up to n unprecedented 1 million compute nodes; and through visualization of network simulation metrics such as link bandwidth, packet latency, and port occupancy, we get an insight into the network behavior at the million-node scale. We also show linear strong scaling of the Slim Fly model on an Intel cluster achieving a peak event rate of 36 million events per second using 128 MPI tasks to process 7 billion events. Detailed analysis of the underlying discrete-event simulation performance shows that a million-node Slim Fly model simulation can execute in 198 seconds on the Intel cluster.

interconnection networks↗

LANL/UTEP Metallurgical Science Center of Excellence Planning

LANL seeks research assistance and skills development in three distinct subject areas over the next three years. Individualized scope and detail implementation schedules will be the first deliverable for these subject areas and will represent a joint determination between LANL SMEs and UTEP faculty based on LANL priority (schedule) and UTEP staffing (faculty and student- graduate and undergraduate) and capability of immediate availability per schedule. LANL will endeavor to make summer internships available to UTEP students within these subject areas: Chemical Sciences, Additive Manufacturing, and Metallurgy: casting and solidification, characterization, and metal purification. Unarticulated but generalized scoping tasks follow within each topical area to indicate that students and technicians familiar with these skill sets are of value and interest in LANL workforce pipeline and the tasks that seek to develop these skill sets are intentional on LANL's part. Consequently, LANL will sponsor 2-3 senior (capstone) projects within these subject areas per year over the three year time period within these task areas and within separations technologies, wet chemical analysis, and analytical characterization and quantification as required by all tasks.

36 MATERIALS SCIENCE↗

Evaluating iterative reconstruction performance in computed tomography

Purpose: Iterative reconstruction (IR) offers notable advantages in computed tomography (CT). However, its performance characterization is complicated by its potentially nonlinear behavior, impacting performance in terms of specific tasks. This study aimed to evaluate the performance of IR with both task-specific and task-generic strategies. Methods: The performance of IR in CT was mathematically assessed with an observer model that predicted the detection accuracy in terms of the detectability index (d′). d′ was calculated based on the properties of the image noise and resolution, the observer, and the detection task. The characterizations of image noise and resolution were extended to accommodate the nonlinearity of IR. A library of tasks was mathematically modeled at a range of sizes (radius 1–4 mm), contrast levels (10–100 HU), and edge profiles (sharp and soft). Unique d′ values were calculated for each task with respect to five radiation exposure levels (volume CT dose index, CTDI{sub vol}: 3.4–64.8 mGy) and four reconstruction algorithms (filtered backprojection reconstruction, FBP; iterative reconstruction in imaging space, IRIS; and sinogram affirmed iterative reconstruction with strengths of 3 and 5, SAFIRE3 and SAFIRE5; all provided by Siemens Healthcare, Forchheim, Germany). The d′ values were translated into the areas under the receiver operating characteristic curve (AUC) to represent human observer performance. For each task and reconstruction algorithm, a threshold dose was derived as the minimum dose required to achieve a threshold AUC of 0.9. A task-specific dose reduction potential of IR was calculated as the difference between the threshold doses for IR and FBP. A task-generic comparison was further made between IR and FBP in terms of the percent of all tasks yielding an AUC higher than the threshold. Results: IR required less dose than FBP to achieve the threshold AUC. In general, SAFIRE5 showed the most significant dose reduction potentials (11–54 mGy, 77%–84%), followed by SAFIRE3 (7–36 mGy, 50%–61%) and IRIS (6–26 mGy, 37%–50%). The dose reduction potentials highly depended on task size and task contrast, with tasks of lower contrasts and smaller sizes, i.e., more challenging tasks, indicating higher dose reductions. Softer edge profile showed higher dose reduction potentials with SAFIRE3 and SAFIRE5, but not with IRIS. The task-generic comparison between IR and FBP demonstrated the overall superiority of IR performance, as IR allowed a larger percent of tasks to exceed the threshold AUC: IRIS, 8%–12%; SAFIRE3, 10%–16%; and SAFIRE5, 20%–33%. The improvement with IR was generally more pronounced at lower dose levels. Conclusions: Expanding beyond traditional contrast and noise based assessments of IR, we performed both task-specific and task-generic evaluations of IR performance. The task-specific evaluation demonstrated the dependency of IR’s dose reduction potential on task attributes, which can be employed to optimize IR for clinical indications with specific range of size and contrast. The task-generic evaluation demonstrated IR’s overall superiority over FBP in terms of the range of tasks exceeding a threshold performance level, which can be employed for general comparisons between algorithms.

60 APPLIED LIFE SCIENCES↗

Multi-Task Learning of Scanning Electron Microscopy and Synthetic Thermal Tomography Images for Detection of Defects in Additively Manufactured Metals

One of the key challenges in laser powder bed fusion (LPBF) additive manufacturing of metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality control in LPBF can be accomplished with non-destructive imaging of the actual 3D-printed structures. Thermal tomography (TT) is a promising non-contact, non-destructive imaging method, which allows for the visualization of subsurface defects in arbitrary-sized metallic structures. However, because imaging is based on heat diffusion, TT images suffer from blurring, which increases with depth. We have been investigating the enhancement of TT imaging capability using machine learning. In this work, we introduce a novel multi-task learning (MTL) approach, which simultaneously performs the classification of synthetic TT images, and segmentation of experimental scanning electron microscopy (SEM) images. Synthetic TT images are obtained from computer simulations of metallic structures with subsurface elliptical-shaped defects, while experimental SEM images are obtained from imaging of LPBF-printed stainless-steel coupons. MTL network is implemented as a shared U-net encoder between the classification and the segmentation tasks. Results of this study show that the MTL network performs better in both the classification of synthetic TT images and the segmentation of SEM images tasks, as compared to the conventional approach when the individual tasks are performed independently of each other.

36 MATERIALS SCIENCE↗

A deep neural network regressor for phase constitution estimation in the high entropy alloy system Al-Co-Cr-Fe-Mn-Nb-Ni

High Entropy Alloys (HEAs) are composed of more than one principal element and constitute a major paradigm in metals research. The HEA space is vast and an exhaustive exploration is improbable. Therefore, a thorough estimation of the phases present in the HEA is of paramount importance for alloy design. Machine Learning presents a feasible and non-expensive method for predicting possible new HEAs on-the-fly. A deep neural network (DNN) model for the elemental system of: Mn, Ni, Fe, Al, Cr, Nb, and Co is developed using a dataset generated by high-throughput computational thermodynamic calculations using Thermo-Calc. The features list used for the neural network is developed based on literature and freely available databases. A feature significance analysis matches the reported HEAs phase constitution trends on elemental properties and further expands it by providing so far-overlooked features. The final regressor has a coefficient of determination ( r 2 ) greater than 0.96 for identifying the most recurrent phases and the functionality is tested by running optimization tasks that simulate those required in alloy design. The DNN developed constitutes an example of an emulator that can be used in fast, real-time materials discovery/design tasks.

36 MATERIALS SCIENCE↗

Assessing Uncertainty in Modeling Stress Corrosion Cracking

This report summarizes the collaboration between Sandia National Laboratories (SNL) and the Nuclear Regulatory Commission (NRC) to improve the state of knowledge on chloride induced stress corrosion cracking (CISCC). The foundation of this work relied on using SNL’s CISCC computer code to assess the current state of knowledge for probabilistically modeling CISCC on stainless steel canisters. This work is presented as three tasks. The first task is exploring and independently comparing crack growth rate (CGR) models typically used in CISCC modeling by the research community. The second task is implementing two of the more conservative CGR models from the first task into SNL’s full CISCC code to understand the impact of the different CGR models on a full probabilistic analysis while studying uncertainty from three key input parameters. The combined work of the first two tasks showed that properly measuring salt deposition rates is impactful to reducing uncertainty when modeling CISCC. The work in Task 2 also showed how probabilistic CGR models can be more appropriate at capturing aleatory uncertainty when modeling SCC. Lastly, appropriate and realistic input parameters relevant for CISCC modeling were documented in the last task as a product of the simulations considered in the first two tasks.

36 MATERIALS SCIENCE↗

Robotic Crane System for the Deconstruction of Chernobyl Unit 4 - 18583

The Chernobyl Nuclear Power Plant (ChNPP) Unit 4 accident occurred on April 26, 1986 leaving a severely damaged reactor building and a highly radioactive area. To minimize the long-term radiological impact to personnel and the environment, Unit 4 was immediately enclosed by a structure named the Object Shelter (OS). To transform the OS into an ecologically safe system, the Shelter Implementation Plan (SIP) was developed in 1997. The most significant SIP tasks was the design and construction of the New Safe Confinement (NSC). The NSC is a 36,000 tonne arch enclosure that includes a suite of process equipment to address the ruins of Unit 4 while assuring the safety of workers, public, and the environment. The NSC has a span of 257 meters, length of 164 meters, and height of 110 meters and is designed for a 100 years life. The New Safe Confinement was slid from its erection area to directly over Unit 4 (a distance of 327 meters) in November 2016. One of the major mechanical handling systems installed in the NSC is the Main Cranes System (MCS), designed and fabricated by PaR Systems (USA). The planned deconstruction activities require the handling of shielded waste disposal casks containing fuel as well as transporting extremely large structural elements -remotely controlled using video surveillance equipment. The lifting activities required the cranes to be tele-robotically controlled to prevent inadvertent collisions, expedite repetitive and high accuracy functions, protect the equipment and structures within the NSC as well as increase the overall effectiveness of the MCS. In addition, due to the elevated radiation levels, remote deconstruction activities will need to be performed. The MCS has design provisions included for a tele-robotically controlled manipulator and a suite of tooling to be used for multiple activities including concrete coring, cutting, debris collection and other heavy demolition activities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗