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FEBRUARY 25, 2020
Web Feature

Forces of Attraction

Weak forces are strong enough to align semiconductor nanoparticles; new understanding may help make more useful materials

Improving nuclear waste storage models by studying the chemistry of material interactions

A female researcher wearing a blue lab coat and heat-resistant safety gloves pours molten glass out of a metal crucible onto a metal tray.

PNNL conducts research into glass, glass-ceramic, grout, metal, and metal-ceramic wasteforms that will withstand corrosion over geologic time.

PNNL | Andrea Starr

WastePD EFRC research on the glass-steel interface was published in Nature Materials

February 3, 2020
February 3, 2020
Highlight

New research unravels the chemistry of how materials in the waste packages used for the disposal of high-level radioactive waste interact in deep geologic repository environments. Having a better understanding of the interactions between materials under various conditions provides more information to make waste storage performance models more robust.

“Many performance models use conservative approaches such as assuming that the steel canister walls don’t even exist or that they dissolve very fast. This study provides the opportunity to better incorporate the canister barrier in the models,” said Joseph Ryan, a PNNL materials scientist and coauthor on the paper, “Self-accelerated corrosion of nuclear waste forms at material interfaces,” published in Nature Materials.

The United States is converting highly radioactive nuclear waste, also known as high-level waste, into glass. The molten glass is poured into steel canisters for long-term storage and ultimate disposal in a geologic repository. The goal is to design waste storage and disposal systems that would remain safe for hundreds of thousands of years to come, even if they are exposed to water. Because of the extensive time span of waste storage, researchers turn to cutting-edge science to project what will happen during that time period. The data is used to inform extensive safety analyses—helping make sure the system is engineered to be compatible with the natural system so that waste remains separate from the environment.

“We can’t just do a test on a material and say, ‘That material corroded this much in 30 days and extrapolate that to a million years.’ It doesn’t work that way,” Ryan said. “At the most basic level, we try to understand the underlying chemistry of corrosion. Then, we feed that information into computer models to calculate the expected release over time.”

In this study, led by the WastePD Energy Frontier Research Center based at Ohio State University, researchers unpacked the chemistry that occurs when two materials are close together, focusing on glass-steel along with ceramic-steel interactions. This chemical situation could occur when water has percolated into the repository and has breached the steel canister, exposing the glass-steel interface to water.

When water finally breaches the waste package container, it will fill the microscopic space that forms between the solid glass and the steel canister. Chemical reactions that happen in localized and tiny microenvironments such as these can be quite different than those happening in a more open setting. In this case, this localized area can have a different chemistry than the surrounding solution, causing more corrosion than would be expected.

The researchers tested their theory in the laboratory. They pressed glass and steel together in salty liquid and kept it at 90° C (194° F) for a month. At the end of the experiment, they found differences in the width of thin layers that indicated higher corrosion between the glass-steel couple interface than in a control sample.

Why it matters: This research allows scientists to improve models that project how a disposal canister could perform in a deep geologic environment. Having a better understanding of the interactions between materials under various conditions provides more information to make the models more robust. Currently, some models project what happens to waste under the assumption that the steel canister walls do not exist. Operating under this pretext can result in higher projections of waste degradation than would likely occur when taking a conservative approach. But better understanding the chemistry of how the solid waste and the steel canister interact allows a scientifically based understanding of how the canisters behave and interact with the glass to be included in performance assessment models.

Summary: High-level waste is immobilized as glass in stainless steel canisters. On cooling, a confined crevice space forms at the stainless steel-glass interface. If the disposal canister is breached and if water can enter the steel-glass interface, it could result in anodic dissolution of the stainless steel, generating metal cations, which hydrolyze to form protons and strongly increase the local acidity. This acidic environment may locally enhance the corrosion of both the stainless steel and the glass, which leads to the release of cations from the glass. Further, the coupled corrosion may trigger the precipitation of additional secondary phases that may impact subsequent canister corrosion or nuclear glass durability.

What’s Next: While this study sheds light on the chemical interactions that occur at the stainless steel-glass interface, there are more interactions to explore. Ultimately, a better understanding of different chemical mechanisms will improve the overall performance model.

Acknowledgements

Sponsors: This work was supported as part of the Center for Performance and Design of Nuclear Waste Forms and Containers, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Basic Energy Sciences under Award no. DESC0016584.

Research Team: Xiaolei Guo, Gerald S. Frankel, Gopal Viswanathan, Tianshu Li (Ohio State University); Stéphane Gin (CEA, France); Penghui Lei, Tiankai Yao, Jie Lian (Rensselaer Polytechnic Institute); Hongshen Liu, Dien Ngo, Seong H. Kim (Pennsylvania State University); Daniel K. Schreiber, John D. Vienna, Joseph V. Ryan (PNNL); Jincheng Du (University of North Texas)

January 27, 2020
JANUARY 10, 2020
Web Feature

Clark Recognized for Nuclear Chemistry Research

The world’s largest scientific society honored Sue B. Clark, a PNNL and WSU chemist, for contributions toward resolving our legacy of radioactive waste, advancing nuclear safeguards, and developing landmark nuclear research capabilities.
DECEMBER 6, 2019
Web Feature

Converging on Coastal Science

Advancing a more collective understanding of coastal systems dynamics and evolution is a formidable scientific challenge. PNNL is meeting the challenge head on to inform decisions for the future.
DECEMBER 4, 2019
Web Feature

A More Painless Extraction

PNNL and Argonne researchers developed and tested a chemical process that successfully captures radioactive byproducts from used nuclear fuel so they could be sent to advanced reactors for destruction while also producing electrical power.
NOVEMBER 5, 2019
Web Feature

Magnesium Takes ShAPE™

Two forms of magnesium material were processed into tubing using PNNL’s Shear Assisted Processing and Extrusion™ technology. Both materials were found to have quite similar and improved properties—even though they began vastly different.

Moments Matter When It Comes to Modeling Rain

Rain

Getting rain properties correct in atmospheric models is critical for accurately representing the structure and evolution of cloud systems.

Improved representation of rain microphysics led to more accurate simulations of surface precipitation

March 12, 2019
October 22, 2019
Highlight

The Science
In atmospheric models, raindrop properties such as rainfall rate are usually described based on the raindrop size distribution. For example, heavy rain rates may have a wider raindrop size distribution than light rain. To improve predictions of rain that reaches the surface, the primary question has been, how can models better represent the evolution of raindrop size distribution in space and time in the atmosphere? A team led by researchers at the U.S. Department of Energy’s (DOE) Pacific Northwest National Laboratory improved the representation of rain microphysics by predicting the shape parameter of raindrop size distributions in a recently developed cloud microphysics scheme. They found that under a wide range of atmospheric conditions, their advanced representation delivered surface rain properties similar to those produced by a benchmark scheme, but with less computational resources.

The Impact
Because raindrops play a major role in the vertical redistribution of heat and moisture in the atmosphere, they are a critical component for modeling the structure and evolution of cloud systems such as mesoscale convective systems. These systems are major sources of heavy rain in the central United States. A proper representation of rain in numerical models is not only vital to predict surface precipitation, but also to accurately simulate environmental conditions and circulation patterns. The advanced rain microphysics representation from this study improves simulations of rain properties under various atmospheric conditions, and it can be used to increase accuracy of weather and climate models. The scheme will be implemented in DOE’s Energy Exascale Earth System Model (E3SM).

Summary
Cloud microphysics schemes in weather and climate models usually predict two moments—the total number and mass—of the raindrop size distribution. Researchers upgraded the Predicted Particle Properties (P3) cloud scheme by adding another predicted variable—shape parameter—for raindrop size distribution, turning the two-moment scheme into a three-moment scheme for raindrop representation. They also developed and incorporated a new parameterization for drop-drop collisions—when two drops collide—and the breakup of large drops into smaller ones. 
To evaluate those new developments, the research team tested them with an idealized rain model. The model simulated 450 rain scenarios that were initialized by different raindrop size distributions and environmental conditions. Researchers compared the simulated surface rain properties against those from a detailed and computationally costly reference scheme. The team found that, depending on initial rain intensity, up to 95 percent of simulations with the new developments produced raindrop sizes and surface rain rates within ±20 percent biases from the reference results. This was a considerable improvement from the original two-moment scheme, which only reached 4 percent using the same criteria for comparisons with the reference results. Sensitivity tests showed that both the added degree of freedom—the additional variable for raindrop size distribution—and the new process parameterization contributed to the improvements.

PI Contact
Jiwen Fan, Pacific Northwest National Laboratory, jiwen.fan@pnnl.gov  

Funding
This research was supported by the Climate Model Development and Validation program funded by the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science. Model simulations were performed using PNNL Institutional Computing.

Paukert M, J Fan, PJ Rasch, H Morrison, JA Milbrandt, J Shpund, and A. Khain. 2019. “Three-Moment Representation of Rain in a Bulk Microphysics Model.” Journal of Advances in Modeling Earth Systems 11(1):257−277, https://doi.org/10.1029/2018MS001512.

Influence of Groundwater Extraction Costs and Resource Depletion Limits on Simulated Global Nonrenewable Water Withdrawals over the 21st Century

Groundwater

Recent PNNL research suggests that rising groundwater extraction costs will force users to turn to other sources of water.

Global groundwater depletion is projected to peak and then decline during this century as costs of using it change

April 16, 2019
October 22, 2019
Highlight

The Science
Because water is a fundamental human need, estimating future supplies is important. Researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) coupled regionally varying groundwater availability and extraction cost estimates with continually adjusted demands for water in a simulation that covered multiple sectors around the world. As groundwater levels dropped, imposing greater capital and energy costs to bring water to the surface, modeled water use sectors responded by drawing from other water resources. These behaviors resulted in a marked peak and decline in the rate of global groundwater depletion.

The Impact
Previously it was assumed that the rate of global groundwater depletion would increase steadily over the 21st century as humans demanded more water—particularly for crop production. This work suggests that groundwater depletion may actually decline, because the increasing costs of pumping will force water users to adapt by turning to less expensive sources, which are often in regions where renewable water remains plentiful.

Summary
In many regions of the world, groundwater reserves are being depleted rapidly. This raises concerns for the sustainability of irrigated agriculture and global food supplies. It is therefore important to study groundwater depletion and possible exhaustion of water resources at a global scale. A problem for such analysis is the lack of detailed understanding of when a depleting resource becomes unviable for further exploitation. The question is not simply how much water is physically available; we need to know when the financial costs and environmental effects of extracting more groundwater render the resource unviable for human applications. To study these effects, PNNL researchers employed a global, gridded data set that specifies the cost of groundwater extraction as a function of depletion. Then, using the Global Change Assessment Model (GCAM), they simulated water users as economic decision makers to understand how they would adapt as extraction costs increased. Results indicated that future rates of global groundwater depletion would be heavily moderated by increasing extraction costs. Regions that depleted water to costly levels lost competitive advantage for crop production, which shifted to regions where water resources were less costly and more plentiful. The team concluded that extraction costs must be included in simulations for projections of global groundwater depletion to be reliable.

PI Contact
Leon Clarke, Pacific Northwest National Laboratory, leon.clarke@pnnl.gov

PNNL Contact
Mohamad Hejazi, Pacific Northwest National Laboratory, Mohamad.Hejazi@pnnl.gov  

Funding
This research was supported by the U.S. Department of Energy Office of Science, Biological and Environmental Research through the Multisector Dynamics, Earth and Environmental System Modeling Program. 

Turner SWD, M Hejazi, C Yonkofski, SH Kim, and P Kyle. 2019. “Influence of Groundwater Extraction Costs and Resource Depletion Limits on Simulated Global Nonrenewable Water Withdrawals Over the Twenty-First Century.” Earth’s Future 7(2):123−135. https://doi.org/10.1029/2018ef001105.

Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning

Bend

The BEND model can combine information on building technologies, climate, and population to forecast hourly building energy demand for regions the size of electric power balancing authorities. This calibration aligns the results with historical data to make them more accurate.

A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in building energy demand

June 6, 2019
October 22, 2019
Highlight

The Science
Aggregated building energy demand models, which are based on combining the outcomes of many individual building simulations, are an emerging tool for long-term energy planning at multiple spatial scales. They can be used to understand and project changes in building energy demand due to changes in population, climate, and building technologies. However, these models can be hard to calibrate because real-world data availability at the appropriate temporal, spatial, and sectoral scales is often limited. A new approach developed at the U.S. Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) allows these aggregate models to be calibrated at multiple scales. Researchers used this new method to calibrate PNNL’s Building ENergy Demand (BEND) aggregate model. Once calibrated, BEND successfully captured year-to-year changes in building energy demand due to changes in weather.

The Impact
Unlike more traditional statistical methods, physically based aggregate models such as BEND can fully capture the dynamic relationships between hourly building energy demand and population, climate, and building technologies. As a result, these models are valuable tools for understanding multisectoral dynamics. The new approach allows BEND and other aggregate models to be calibrated at the scale at which they will be applied, overcoming a key limitation of this class of models. Models such as BEND will improve model projections of future building energy demand at different scales and refine long-term energy planning through integration with grid operations and resource planning models.

Summary
PNNL’s BEND model is one of an emerging class of models designed to capture total and hourly building energy demand resulting from the aggregation of tens to hundreds of thousands of individual building simulations. Historically, these aggregate models have proven difficult to calibrate because there is a limited amount of target data available at relevant space, time, and sectoral scales. Researchers developed and demonstrated a novel approach to calibrate BEND, using approximately 100,000 individual simulations of DOE’s EnergyPlus model, against the best available data at the geographic scale of balancing authorities (electricity management subregions). Once calibrated, BEND captured year-to-year changes in total and peak building energy demand due to variations in weather within these areas. The study applied PNNL’s new calibration approach to the western United States, but the method can be applied to regions across the world with similar data and scale challenges. Researchers also suggested areas in which improved data collection and sharing would help to further refine these emerging models.

PI Contact
Jennie Rice, Pacific Northwest National Laboratory, jennie.rice@pnnl.gov
Ian Kraucunas, Pacific Northwest National Laboratory, ian.kraucunas@pnnl.gov 

Funding
This research was supported by the DOE Office of Science as part of research in the MultiSector Dynamics, Earth and Environmental System Modeling Program. A portion of the research was performed using PNNL’s Institutional Computing resources. 

Taylor ZT, Y Xie, CD Burleyson, N Voisin, and I Kraucunas. 2019. “A multi-scale calibration approach for process-oriented aggregated building energy demand models.” Energy and Buildings 191:82‒94. https://doi.org/10.1016/j.enbuild.2019.02.018.

A Global Hydrologic Framework to Accelerate Scientific Discovery

Hydro

A new version of the Xanthos global hydrology model enables researchers to rapidly address complex multisector dynamics science challenges, such as determining water scarcity impacts on land use, and could help accelerate energy-water-land research even more.

A new version of the Xanthos model enables researchers to rapidly address evolving energy-water-land science challenges

June 11, 2019
October 22, 2019
Highlight

The Science
Research in energy-water-land systems—and understanding how water scarcity can affect these systems—is rapidly progressing. To quantify changes in—and the effects of—future freshwater availability, a team from the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) developed the Xanthos global hydrology model, which can be used independently or as a part of a coupled modeling system. Researchers can use Xanthos to explore how different climate, socioeconomic, or energy scenarios affect regional and global water availability over the 21st century. In version 2 of the model, the PNNL team built a component-based framework to rapidly incorporate and test new hydrologic process modules—or code—within a robust environment, complete with diagnostics and calibration capabilities.

The Impact
Within Xanthos version 2, scientists can easily incorporate and test evolving hydrologic process models as components, or selectable, compatible parts of the Xanthos framework. For example, researchers can customize a specific configuration of components to address the role of snowmelt in characterizing drought or to explore the role of model assumptions in characterizing the uncertainty of complex coupled energy-water-land systems. The process of incorporating and testing models within the component-based framework is faster than what it would take to reproduce an entire configuration of models if users added their own from scratch. The usability of Xanthos version 2 enables researchers to rapidly address complex multisector dynamics science challenges, such as determining water scarcity impacts on land use, and could help accelerate energy-water-land research even more.

Summary
Xanthos, an open-source model written in Python, provides a solid foundation for continued advances in global water dynamics science. The model simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos also can serve as the freshwater supply component of the Global Change Assessment Model (GCAM), also developed at PNNL. 
For Xanthos version 2, the PNNL team built upon the original version by creating a component-based framework in which users can swap out or extend previously existing core components of the model—potential evapotranspiration (PET), runoff generation, and river routing—without starting from scratch. For example, users can now swap out the potential evapotranspiration core component with one they think captures the dynamics of the systems and processes they are trying to model. The component-style architecture of Xanthos version 2 enables researchers to quickly incorporate and test the latest energy-water-land research in a stable modeling environment with prebuilt diagnostics. The PNNL team also created a robust default configuration that includes a calibration module, hydropower modules, and new PET modules. These enhancements are now available to the scientific community in Xanthos version 2, which can be downloaded from GitHub.

PI Contact
Mohamad Hejazi, Pacific Northwest National Laboratory, Mohamad.Hejazi@pnnl.gov

Funding
This research was supported by the U.S. Department of Energy Office of Science as part of research in the MultiSector Dynamics, Earth and Environmental System Modeling program.

Vernon CR, MI Hejazi, SWD Turner, Y Liu, CJ Braun, X Li, and RP Link. 2019. “A Global Hydrologic Framework to Accelerate Scientific Discovery.” Journal of Open Research Software 7(1):1, http://doi.org/10.5334/jors.245.

Making 1+1 Bigger than 2

modules

A study highlighted progress and pitfalls in coupling different modules within weather, climate, and Earth system models, demonstrating the pervasiveness of coupling problems in current models as well as highlighting recent progress.

A state-of-the-science review highlighted progress and pitfalls in coupling different modules within weather, climate, and Earth system models

February 18, 2019
October 22, 2019
Highlight

The Science
Modern computer models for weather, climate, and Earth systems contain numerous modules that simulate the complex workings of distinct physical and dynamical phenomena, such as ocean currents, atmospheric winds, clouds, and river flows. These individual modules are typically developed by separate groups of researchers and then connected to form a comprehensive model system. The two-step approach can lead to inaccurate results in current model simulations. An international team of researchers, including scientists from the U.S. Department of Energy’s Pacific Northwest National Laboratory, reviewed the state of the science in module coupling and identified possible ways to address some key challenges.

The Impact
Most model development work typically focuses on individual modules, resulting in a research gap in the simulation of weather and climate, which are the sum of many processes. This review paper demonstrates the pervasiveness of coupling problems in current models and highlights recent progress in module coupling. The paper also provides illustrative examples of coupling issues, such as insufficient frequency of information exchange between modules and double counting of processes by multiple modules. Such issues could, for example, strongly affect how much rain is predicted in a simulation of storms. The coupling issues must be overcome for each module to realize its full potential and improve the overall predictive skill of the entire model system. This is needed for the improvement of existing modules as well as in the design of new modules or model systems. 

Summary
The compartmentalization of model codes and development teams is natural and also necessary to manage the endeavor of modeling complex weather, climate, and Earth systems, which are influenced by many processes. As a result, three types of issues can occur: First, the artificial distinction between physical phenomena based on whether they can be spatially resolved or not can lead to double counting or undercounting of processes. Second, infrequent information exchange between interacting modules can result in biases, or offsets from observations, in the balance between them. Third, inconsistent approximations employed by different modules can lead to unintended violation of basic physical principles. The topic of coupling typically receives little attention during model development, and more evidence suggests that this gap in research is becoming a bottleneck in further improving the corresponding models.
Aimed at increasing awareness of such issues, this review describes the symptoms of coupling problems using examples from existing literature and discusses their root causes and possible methods for analyzing the problems. The paper reflects the findings of many research highlights from an international biennial workshop series on physics-dynamics coupling. Since the first workshop in 2014, this small but evolving event series has gained attention from international weather, climate and Earth system model development groups and research sponsors to join forward-thinking discussions and address the ubiquitous coupling problems. Topics discussed in the workshop series and the paper include: conceptual inconsistencies in model equations; numerical methods for solving the equations with computers; sensitivities of model results to choices made for the numerical calculations and strategies for analyzing such sensitivities; and methods for making the computations more efficient on supercomputers.

PNNL Contacts
Hui Wan, Pacific Northwest National Laboratory, Hui.Wan@pnnl.gov
L. Ruby Leung, Pacific Northwest National Laboratory, Ruby.Leung@pnnl.gov

Funding
The U.S. Department of Energy (DOE) Office of Science funded Hui Wan’s, Peter M. Caldwell’s, and Philip J. Rasch’s contributions to the paper as part of the Scientific Discovery through Advanced Computing (SciDAC) program. PNNL’s Linus Pauling Distinguished Postdoctoral Fellowship partially supported earlier contributions by Hui Wan. DOE Office of Science Grants DE-SC0006684 and DE-SC0003990 supported Christiane Jablonowski and Diana R. Thatcher. The DOE Office of Science, Biological and Environmental Research funded Koichi Sakaguchi’s and L. Ruby Leung’s contribution to this work as part of the Regional and Global Model Analysis, Earth and Environmental System Modeling program. Part of the numerical simulations presented in the paper used computational resources from the National Energy Research Scientific Computing Center (NERSC), a DOE user facility supported by the Office of Science under Contract DE-AC02-05CH11231, and PNNL Institutional Computing.

Gross M, H Wan, PJ Rasch, PM Caldwell, DL Williamson, D Klocke, C Jablonowski, DR Thatcher, N Wood, M Cullen, B Beare, M Willett, F Lemarié, E Blayo, S Malardel, P Termonia, A Gassmann, PH Lauritzen, H Johansen, CM Zarzycki, K Sakaguchi, and R Leung. 2018. “Physics–Dynamics Coupling in Weather, Climate, and Earth System Models: Challenges and Recent Progress.” Monthly Weather Review 146:3505–3544, https://doi.org/10.1175/MWR-D-17-0345.1.