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DOE OSTI2021

Regulation of dhurrin pathway gene expression during Sorghum bicolor development

Plant defence models evaluate the costs and benefits of resource investments at different stages in the life cycle. Poor understanding of the molecular regulation of defence deployment and remobilization hampers accuracy of the predictions. Cyanogenic glucosides, such as dhurrin are phytoanticipins that release hydrogen cyanide upon bio-activation. In this study, RNA-seq was used to investigate the expression of genes involved in the biosynthesis, bio-activation and recycling of dhurrin in Sorghum bicolor . Genes involved in dhurrin biosynthesis were highly expressed in all young developing vegetative tissues (leaves, leaf sheath, roots, stems), tiller buds and imbibing seeds and showed gene specific peaks of expression in leaves during diel cycles. Genes involved in dhurrin bio-activation were expressed early in organ development with organ-specific expression patterns. Genes involved in recycling were expressed at similar levels in the different organ during development, although post-floral initiation when nutrients are remobilized for grain filling, expression of GSTL1 decreased > tenfold in leaves and NITB2 increased > tenfold in stems. Results are consistent with the establishment of a pre-emptive defence in young tissues and regulated recycling related to organ senescence and increased demand for nitrogen during grain filling. This detailed characterization of the transcriptional regulation of dhurrin biosynthesis, bioactivation and remobilization genes during organ and plant development will aid elucidation of gene regulatory networks and signalling pathways that modulate gene expression and dhurrin levels. In-depth knowledge of dhurrin metabolism could improve the yield, nitrogen use efficiency and stress resilience of Sorghum .

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

A Review of Machine Learning Classification Using Quantum Annealing for Real-World Applications

Optimizing the training of a machine learning pipeline helps in reducing training costs and improving model performance. One such optimizing strategy is quantum annealing, which is an emerging computing paradigm that has shown potential in optimizing the training of a machine learning model. The implementation of a physical quantum annealer has been realized by D-wave systems and is available to the research community for experiments. Recent experimental results on a variety of machine learning applications using quantum annealing have shown interesting results where the performance of classical machine learning techniques is limited by limited training data and high dimensional features. This article explores the application of D-wave’s quantum annealer for optimizing machine learning pipelines for real-world classification problems. Finally, we review the application domains on which a physical quantum annealer has been used to train machine learning classifiers. We discuss and analyze the experiments performed on the D-Wave quantum annealer for applications such as image recognition, remote sensing imagery, computational biology, and particle physics. We discuss the possible advantages and the problems for which quantum annealing is likely to be advantageous over classical computation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation

In this paper, we present mixed integer linear programming (MILP) formulations to obtain optimal sizing for a battery energy storage system (BESS) and solar generation system in an extreme fast charging station (XFCS) to reduce the annualized total cost. The proposed model characterizes a typical year with eight representative scenarios and obtains the optimal energy management for the station and BESS operation to exploit the energy arbitrage for each scenario. Contrasting extant literature, this paper proposes a constant power constant voltage (CPCV) based improved probabilistic approach to model the XFCS charging demand for weekdays and weekends. This paper also accounts for the monthly and annual demand charges based on realistic utility tariffs. Furthermore, BESS life degradation is considered in the model to ensure no replacement is needed during the considered planning horizon. Different from the literature, this paper offers pragmatic MILP formulations to tally BESS charge/discharge cycles using the cumulative charge/discharge energy concept. McCormick relaxations and the Big-M method are utilized to relax the bi-linear terms in the BESS operational constraints. Finally, a robust optimization-based MILP model is proposed and leveraged to account for uncertainties in electricity price, solar generation, and XFCS demand. Case studies were performed to signify the efficacy of the proposed formulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

A projection-based analytical Jacobian framework for chemical kinetics applications

A major challenge in simulating complex combustion systems with detailed chemical kinetic models is the cost of integrating the chemical source terms, often done using stiff ODE solvers that require frequent Jacobian evaluations. Using analytically derived Jacobian matrices instead of divided-difference-based numerical Jacobian approximations can significantly reduce the associated computational cost. However, ambiguities arise in the formulation of analytical Jacobians because the chemical state of the system, or state vector, can be expressed in multiple ways, involving variables that are typically not independent from one another. Here, in this work, the consequences of those ambiguities on practical calculations are characterized in detail, and a generalized, projection-based framework is proposed as a mitigation strategy. Performances are assessed in a series of test cases involving a variety of configurations and numerical solution approaches. Results show that with proper treatment, commonly used analytical Jacobian formulations can be considered as equivalent for practical purposes, thereby alleviating concerns that the state vector chosen to express the governing equations and corresponding analytical Jacobian may significantly impact the accuracy of the simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Development of an enzyme cocktail to bioconvert untapped starch in sweet sorghum processing by-products: Part II. Application and economic potential

Demand for bioethanol and other biochemicals produced from agricultural crops has increased. Sweet sorghum has been identified as a promising bioenergy crop as it can produce starch, sugar, and fibrous biomass. During processing, starch accumulates in the juice sediments and clarification mud. And, while currently not recovered, it can be made accessible for fermentation by enzymatic hydrolysis. The enzymatic hydrolysis of starch in sweet sorghum processing streams was investigated, followed by fermentation of the resulting glucose to ethanol. The juice sediment contained sufficient starch to increase fermentable sugars by 127%, allowing a final ethanol titer of 11.1 vol%. The economics for fermentation of only dissolved sugars (Scenario 1) versus dissolved sugars and hydrolyzed starch (Scenario 2) were compared using a technoeconomic model. Fixed capital cost was found to be similar for both scenarios. For a set harvest period, Scenario 2 could produce 20% more ethanol; however, if the distillation by-product was dried and marketed as animal feed, Scenario 1 was more cost effective. A plant producing 5.6–5.7 Mkg of fuel ethanol per year had a minimum selling price of $0.67/kg of ethanol with concurrent production of animal feed and zero cost sweet sorghum processing. Finally, even with these optimistic assumptions, the estimated production cost was higher than the current wholesale price of fuel ethanol.

09 BIOMASS FUELS↗

DOE OSTI2016

Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction

Two prime bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. However, incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting—both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We introduce and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Analysis of hematite attrition in a grid jet apparatus

Particulate attrition is of interest for novel carbon-capture processes such as chemical looping combustion because the makeup cost of oxygen carrier is a significant portion of operating cost. As such, models to study and predict attrition of various oxygen carriers in fluidized bed systems are being developed. One of the regions of concern in fluidized bed systems is the high-velocity jet region near gas distributors in a fluid bed. This work studies the attrition of hematite particles using a modified ASTM apparatus to measure the particle size distribution throughout the experiment. Bed weight and gas velocity were varied. Hematite particles above the corresponding threshold value had a severe variation of particle size distributions which decreased with time. Weight fractions of the sieves over time were fit to a linear, time-variant population balance model to offer insight into particle attrition. The first-order rate constant was modified as a decaying exponential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Silibinin, dexamethasone, and doxycycline as potential therapeutic agents for treating vesicant-inflicted ocular injuries

There are no effective and approved therapies against devastating ocular injuries caused by vesicating chemical agents sulfur mustard (SM) and nitrogen mustard (NM). Herein, studies were carried out in rabbit corneal cultures to establish relevant ocular injury biomarkers with NM for screening potential efficacious agents in laboratory settings. NM (100 nmol) exposure of the corneas for 2 h (cultured for 24 h), showed increases in epithelial thickness, ulceration, apoptotic cell death, epithelial detachment microbullae formation, and the levels of VEGF, cyclooxygenase-2 (COX-2) and matrix metalloproteinase-9 (MMP-9). Employing these biomarkers, efficacy studies were performed with agent treatments 2 h and every 4 h thereafter, for 24 h following NM exposure. Three agents were evaluated, including prescription drugs dexamethasone (0.1%; anti-inflammatory steroid) and doxycycline (100 nmol; antibiotic and MMP inhibitor) that have been studied earlier for treating vesicant-induced eye injuries. We also examined silibinin (100 μg), a non-toxic natural flavanone found to be effective in treating SM analog-induced skin injuries in our earlier studies. Treatments of doxycycline + dexamethasone, and silibinin were more effective than doxycycline or dexamethasone alone in reversing NM-induced epithelial thickening, microbullae formation, apoptotic cell death, and MMP-9 elevation. However, dexamethasone and silibinin alone were more effective in reversing NM-induced VEGF levels. Doxycycline, dexamethasone and silibinin were all effective in reversing NM-induced COX-2 levels. Apart from therapeutic efficacy of doxycycline and dexamethasone, these results show strong multifunctional efficacy of silibinin in reversing NM-induced ocular injuries, which could help develop effective and safe therapeutics against ocular injuries by vesicants. -- Highlights: ► Established injury biomarkers in rabbit corneal culture with nitrogen mustard (NM) ► This NM model is a cost effective system to evaluate and optimize therapeutics. ► Show that doxycycline and dexamethasone reduce NM-caused ocular injuries ► Demonstrate that silibinin effectively reverses NM-caused ocular injury endpoints ► Suggest optimization of identified agents against ocular injuries by vesicants.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

The climate and air-quality benefits of wind and solar power in the United States

Wind and solar energy reduce combustion-based electricity generation and provide air-quality and greenhouse gas emission benefits. These benefits vary dramatically by region and over time. From 2007 to 2015, solar and wind power deployment increased rapidly while regulatory changes and fossil fuel price changes led to steep cuts in overall power-sector emissions. In this paper, we evaluate how wind and solar climate and air-quality benefits evolved during this time period. We find cumulative wind and solar air-quality benefits of 2015 US$29.7–112.8 billion mostly from 3,000 to 12,700 avoided premature mortalities, and cumulative climate benefits of 2015 US5.3–106.8 billion. The ranges span results across a suite of air-quality and health impact models and social cost of carbon estimates. Finally, we find that binding cap-and-trade pollutant markets may reduce these cumulative benefits by up to 16%. In 2015, based on central estimates, combined marginal benefits equal 7.3 ¢ kWh -1 (wind) and 4.0 ¢ kWh -1 (solar).

14 SOLAR ENERGY↗

DOE OSTI2025

Machine learning of 27Al NMR electric field gradient tensors for crystalline structures from DFT

NMR crystallography has emerged as a promising technique for the determination and refinement of atomic coordinates in crystal structures. The crystal structure of compounds containing quadrupolar nuclei, such as 27Al, can be improved by directly comparing solid-state NMR measurements to DFT computations of the electric field gradient (EFG) tensor. The non-negligible computational cost of these first-principles calculations limits the applicability of this method to all but the most well-defined structures. We developed a fast, low-cost machine learning model to predict EFG parameters based on local structural motifs and elemental parameters. We computed 8081 EFG tensors from 1681 27Al crystalline solids using DFT and benchmarked them against 105 experimentally measured 27Al sites. Surprisingly, simple local geometric features dominate the predictive performance of the resulting random-forest model, yielding an R2 value of 0.98 and an RMSE of 0.61 MHz for CQ, the quadrupolar coupling constant. This model accuracy should enable pre-refining future structural assignments before finally validating with first-principles calculations. Such a catalogue of 27Al NMR tensors can serve as a tool for researchers assigning complex NMR spectra influenced by the nuclear electric quadrupole interaction.

Sun, He↗

DOE OSTI2014

The mechanics of motorised momentum exchange tethers when applied to active debris removal from LEO

The concept of momentum exchange when applied to space tethers for propulsion is well established, and a considerable body of literature now exists on the on-orbit modelling, the dynamics, and also the control of a large range of tether system applications. The authors consider here a new application for the Motorised Momentum Exchange Tether by highlighting three key stages of development leading to a conceptualisation that can subsequently be developed into a technology for Active Debris Removal. The paper starts with a study of the on-orbit mechanics of a full sized motorised tether in which it is shown that a laden and therefore highly massasymmetrical tether can still be forced to spin, and certainly to librate, thereby confirming its possible usefulness for active debris removal (ADR). The second part of the paper concentrates on the modelling of the centripetal deployment of a symmetrical MMET in order to get it initialized for debris removal operations, and the third and final part of the paper provides an entry into scale modelling for low cost mission design and testing. It is shown that the motorised momentum exchange tether offers a potential solution to the removal of large pieces of orbital debris, and that dynamic methodologies can be implemented to in order to optimise the emergent design.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

1D PIC-DSMC analysis of a high-pressure nanosecond pulse discharge breakdown in helium

Kinetic simulations of plasma phenomena during and after formation of the conductive plasma channel of a nanosecond pulse discharge are analyzed and compared to existing experimental measurements. Particle-in-cell with direct simulation Monte Carlo collisions (PIC-DSMC) modeling is used to analyze a discharge in helium at 200 Torr and 300 K over a 1 cm gap. The analysis focuses on physics that would not be reproduced by fluid models commonly used at this high number density and collisionality, specifically non-local and stochastic phenomena. Similar analysis could be used to improve the predictive capability of lower fidelity or reduced order models. First, the modeling results compare favorably with experimental measurements of electron number density, temperature, and 1D electron energy distribution function at the same conditions. Second, it is shown that the ionization wave propagates in a stochastic, stepwise manner, dependent on rare, random ionization events ahead of the ionization wave when the ionization fraction in front of the ionization wave is very low, analagous to the stochastic branching of streamers in 3D. Third, analysis shows high-energy runaway electrons accelerated in the cathode layer produce electron densities in the negative glow region over an order of magnitude above those in the positive column. Finally, future work to develop reduced order models of these two phenomena would improve the accuracy of fluid plasma models without the cost of PIC-DSMC simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Balancing unevenly distributed data in seismic tomography: a global adjoint tomography example

SUMMARY The uneven distribution of earthquakes and stations in seismic tomography leads to slower convergence of nonlinear inversions and spatial bias in inversion results. Including dense regional arrays, such as USArray or Hi-Net, in global tomography causes severe convergence and spatial bias problems, against which conventional pre-conditioning schemes are ineffective. To save computational cost and reduce model bias, we propose a new strategy based on a geographical weighting of sources and receivers. Unlike approaches based on ray density or the Voronoi tessellation, this method scales to large full-waveform inversion problems and avoids instabilities at the edges of dense receiver or source clusters. We validate our strategy using a 2-D global waveform inversion test and show that the new weighting scheme leads to a nearly twofold reduction in model error and much faster convergence relative to a conventionally pre-conditioned inversion. We implement this geographical weighting strategy for global adjoint tomography.

Ruan, Youyi↗

DOE OSTI2020

STRIDES: a 3.9 per cent measurement of the Hubble constant from the strong lens system DES J0408−5354

We present a blind time-delay cosmographic analysis for the lens system DES J0408−5354. This system is extraordinary for the presence of two sets of multiple images at different redshifts, which provide the opportunity to obtain more information at the cost of increased modelling complexity with respect to previously analysed systems. We perform detailed modelling of the mass distribution for this lens system using three band Hubble Space Telescope imaging. We combine the measured time delays, line-of-sight central velocity dispersion of the deflector, and statistically constrained external convergence with our lens models to estimate two cosmological distances. We measure the ‘effective’ time-delay distance corresponding to the redshifts of the deflector and the lensed quasar |$D_{\Delta t}^{\rm eff}=$||$3382_{-115}^{+146}$| Mpc and the angular diameter distance to the deflector D_d = |$1711_{-280}^{+376}$| Mpc, with covariance between the two distances. From these constraints on the cosmological distances, we infer the Hubble constant H_0= |$74.2_{-3.0}^{+2.7}$| km s^−1 Mpc^−^1 assuming a flat ΛCDM cosmology and a uniform prior for Ω_m as |$\Omega _{\rm m} \sim \mathcal {U}(0.05, 0.5)$|⁠. This measurement gives the most precise constraint on H_0 to date from a single lens. Our measurement is consistent with that obtained from the previous sample of six lenses analysed by the H_0 Lenses in COSMOGRAIL’s Wellspring (H0LiCOW) collaboration. It is also consistent with measurements of H_0 based on the local distance ladder, reinforcing the tension with the inference from early Universe probes, for example, with 2.2σ discrepancy from the cosmic microwave background measurement.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Optimization of an in Vitro CYP450 Induction Assay Using Cryopreserved Cell Lines

Cytochrome P450 (CYP450) enzymes are responsible for the majority for Phase I metabolism. Induction occurs when a drug increases the rate of CYP450 enzyme production. As a result, the rates of metabolism of subsequent drugs increase, posing concerns for dosing and safety. To further expand the USAMRICD Absorption, Distribution, Metabolism, Excretion, and Toxicity Center of Excellence (ADMET CoE) profiling capabilities, a CYP450 induction assay is being developed using alternative cell lines to primary human hepatocytes to measure changes in gene expression of CYP1A2 and CYP3A4 isoenzymes. Primary human hepatocytes are the gold standard for evaluating P450 induction in vitro ; however, they have inherent limitations such as high costs, fastidious nature, and significant lot‐to‐lot variability. Induction assessments using cryopreserved hepatocytes and two immortalized cell lines, HepaRG and HepatoCells, are being conducted to determine a more robust, cost‐effective alternative model. Each cell line was exposed to the standard inducers rifampicin and omeprazole to assess CYP3A4 and CYP1A2 activity, respectively. Following a 72‐hour incubation period, RNA from the cell cultures was extracted and purified. Fold changes of gene expression were measured using real‐time quantitative PCR (RT‐qPCR). Hepatocytes displayed an average fold change of 92.7 for CYP3A4 and 49.6 for CYP1A2, whereas HepaRG displayed changes of 28.6 and 179.5, respectively. Average values for CYP3A4 and CYP1A2 for HepatoCells were 58.7 and 43.9. Based on the data, HepatoCells most closely mimicked cryopreserved hepatocytes in comparison to HepaRG cells. Additional data on assay parameters and technique optimization will be presented. Support or Funding Information Opinion disclaimer: The views expressed in this abstract are those of the authors and do not reflect the official policy of the Department of the Army, Department of Defense, or the U.S. Government. This project was generously supported in part by an appointment to the Postgraduate Research Participation Program at the U.S. Army Medical Research Institute of Chemical Defense administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and U.S. Army Medical Research and Materiel Command. Support is also provided by the Defense Threat Reduction Agency – Joint Science and Technology Office, Medical S&T Division. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Lim, Tae Young↗

DOE OSTI2024

Rapid Characterization and Statistical Analysis of High-Volume Field-Harvested Photovoltaic Connectors

Photovoltaic (PV) installations heavily depend on connectors for efficient module and string interconnections without requiring skilled labor. Yet this seemingly innocuous component of PV systems is a leading cause of module failures, multiple high-profile fires, and lawsuits in the PV industry. This work aims to answer critical questions regarding why connectors fail and the contributing factors to their failure. The study involves collecting and analyzing more than 17,000 field-harvested connectors from various solar installations across the United States. The vast dataset, which includes connector metadata, visual inspections, and resistance measurements, provides unprecedented insight into the state of health of PV connectors across the US, including the geographic locations, connector types, and installation practices most prone to failures. The work presented here describes a novel rapid characterization method for processing large numbers of connectors and is supported by parallel forensic analysis to discern the root causes of failures as well as a levelized cost of lifetime model to determine the economic ramifications of connector failure. Ultimately, the findings may inform PV developers about the best practices to extend connector longevity and lead to more resilient and reliable PV systems.

connectors↗

DOE OSTI2022

Economic evaluation of the Hepatitis C virus elimination program in the country of Georgia, 2015 to 2017

Abstract Background and Aims In 2015, the country of Georgia launched an elimination program aiming to reduce the prevalence of Hepatitis C virus (HCV) infection by 90% from 5.4% prevalence (~150 000 people). During the first 2.5 years of the program, 770 832 people were screened, 48 575 were diagnosed with active HCV infection, and 41 483 patients were treated with direct‐acting antiviral (DAA)‐based regimens, with a >95% cure rate. Methods We modelled the incremental cost‐effectiveness ratio (ICER) of HCV screening, diagnosis and treatment between April 2015 and November 2017 compared to no treatment, in terms of cost per quality‐adjusted life year (QALY) gained in 2017 US dollars, with a 3% discount rate over 25 years. We compared the ICER to willingness‐to‐pay (WTP) thresholds of US$4357 (GDP) and US$871 (opportunity cost) per QALY gained. Results The average cost of screening, HCV viremia testing, and treatment per patient treated was $386 to the provider, $225 to the patient and $1042 for generic DAAs. At 3% discount, 0.57 QALYs were gained per patient treated. The ICER from the perspective of the provider including generic DAAs was $2285 per QALY gained, which is cost‐effective at the $4357 WTP threshold, while if patient costs are included, it is just above the threshold at $4398/QALY. All other scenarios examined in sensitivity analyses remain cost‐effective except for assuming a shorter time horizon to the end of 2025 or including the list price DAA cost. Reducing or excluding DAA costs reduced the ICER below the opportunity‐cost WTP threshold. Conclusions The Georgian HCV elimination program provides valuable evidence that national programs for scaling up HCV screening and treatment for achieving HCV elimination can be cost‐effective.

Tskhomelidze, Irina↗

DOE OSTI2013

Progress on the decommissioning of Zion nuclear generating station

The decommissioning of the twin 1040 MWe PWRs at Zion, near Chicago USA is a ground breaking programme. The original owner, Exelon Nuclear Corporation, transferred the full responsibility for reactor dismantling and site license termination to a subsidiary of EnergySolutions. The target end state of the Zion site for return to Exelon will be a green field with the exception of the dry fuel storage pad. In return, ZionSolutions has access to the full value of the decommissioning trust fund. There are two potential attractions of this model: lower overall cost and significant schedule acceleration. The Zion programme which commenced in September 2010 is designed to return the cleared site with an Independent Spent Fuel Storage Installation (ISFSI) pad in 2020, 12 years earlier than planned by Exelon. The overall cost, at $500 M per full size power reactor is significantly below the long run trend of $750 M+ per PWR. Implementation of the accelerated programme has been underway for nearly three years and is making good progress. The programme is characterised by numerous projects proceeding in parallel. The critical path is defined by the inspection and removal of fuel from the pond and transfer into dry fuel storage casks on the ISFSI pad and completion of RPV segmentation. Fuel loading is expected to commence in mid- 2013 with completion in late 2014. In parallel, ZionSolutions is proceeding with the segmentation of the Reactor Vessel (RV) and internals in both Units. Removal of large components from Unit 1 is underway. Numerous other projects are underway or have been completed to date. They include access openings into both containments, installation of heavy lift crane capacity, rail upgrades to support waste removal from the site, radiological characterization of facilities and equipment and numerous related tasks. As at February 2013, the programme is just ahead of schedule and within the latest budget. The paper will provide a fuller update. The first two years of the Zion programme offer some interesting learning opportunities. The critical importance of leadership and project control systems will be emphasised in the paper. Strong supplier relationships and good community cooperation are essential. A learning and adaptable team, incentivised to meet schedule and budget, drives affordability of the whole programme. Our key lessons so far concern organisation and people as much as engineering and technology. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗