20 Aug 2020

PUBLICATION NOTICE: Evaluating Collection Parameters for Mobile Lidar Surveys in Vegetated Beach-Dune Settings

Purpose: The goal of this Coastal and Hydraulics Engineering Technical Note (CHETN) is to compare collection parameters and gridding techniques for mobile lidar surveys of beach-dune systems in the northern Outer Banks, NC.

20 Aug 2020

PUBLICATION NOTICE: Utilizing Stream Flows to Forecast Dredging Requirements

Abstract: In recent years, the United States Army Corps of Engineers (USACE) has spent an average of approximately a billion dollars annually for navigation channel maintenance dredging. To execute these funds effectively, USACE districts must determine which navigation channels are most in need of maintenance dredging each year. Traditionally, dredging volume estimates for Operations and Maintenance budget development are based on experiential knowledge and historic averages, with the effects of upstream, precipitation-driven streamflows considered via general-rule approximations. This study uses the Streamflow Prediction Tool, a hydrologic routing model driven by global weather forecast ensembles, and dredging records from the USACE Galveston District to explore relationships between precipitation-driven inland channel flow and subsequent dredged volumes in the downstream coastal channel reaches. Spatially based regression relationships are established between cumulative inland flows and dredged volumes. Results in the test cases of the Houston Ship Channel and the Sabine-Neches Waterway in Texas indicate useful correlations between the computed streamflow volumes and recorded dredged volumes. These relationships are stronger for channel reaches farther inland, upstream of the coastal processes that are not included in the precipitation-driven hydrologic model.

20 Aug 2020

PUBLICATION NOTICE: Three Rivers, Southeast Arkansas Navigation Study: Ship Simulation Report

Abstract: The McClellan-Kerr Arkansas River System (MKARNS) is a major inland waterway that begins at the Port of Catoosa in Tulsa, OK, and travels to the confluence of the White and Mississippi Rivers. Over the years, many structures have been built to help control overland flow between the White, Arkansas, and Mississippi Rivers. These structures have required a significant amount of rehabilitation, which has resulted in high maintenance costs. The US Army Corps of Engineers and the Arkansas Waterways Commission conducted the Three Rivers Southeast Arkansas Feasibility Study (also known as the Three Rivers Study). The Three Rivers Study focused on providing long-term dependable navigation in the MKARNS. From this study, a proposal was developed that included a 1,000 ft reopening of the Historic Cutoff and a reinforcement of several areas near the White River. In 2019, the US Army Engineer Research and Development Center Ship/Tow Simulator was used to perform a navigation study to ensure the proposed modifications did not negatively impact navigation on the White River section of the MKARNS. Assessment of the proposed modifications was accomplished through analysis of ship simulations completed by experienced pilots, discussions, track plots, run sheets, and final pilot surveys.

20 Aug 2020

PUBLICATION NOTICE: A Proposed Ecosystem Services Analysis Framework for the U.S. Army Corps of Engineers

Abstract: Ecosystem goods and services (EGS) have been promoted as a way to effectively examine tradeoffs and improve communication of project-related environmental outcomes in terms of human well-being. This document proposes a framework to inform the development of any future guidance to U.S. Army Corps of Engineers (USACE) District planners for projecting changes in EGS from proposed civil works activities. The framework offers an analytical and communications approach for incorporating EGS in USACE decision-support processes. The core of the framework is a conceptual model that establishes a series of causal relationships that link management actions to EGS benefits/damages, applying economic concepts in both monetary and non-monetary benefit relevant indicators. The six-step planning process is used to demonstrate how the EGS framework might be integrated into existing analytic approaches and modified to fit different levels of resource availability and decision contexts. A hypothetical case study is used to demonstrate analytic techniques. The framework is compatible with goals to create a single decision-support document covering National Environmental Policy Act requirements and planning objectives when comparing project alternatives. The example is intended to generally illustrate the use of EGS in any type of program planning or project evaluation.

20 Aug 2020

PUBLICATION NOTICE: Concept for Artificial Freezing of Sea Ice at Winter Quarters Bay, Antarctica

ABSTRACT:  McMurdo Station serves as a major research and logistics hub for the United States Antarctic Program (USAP). Adjacent to the Station is Winter Quarters Bay (WQB), where vessels dock to unload cargo and fuel. The ice pier at McMurdo is essential for this annual vessel resupply but represents a failure potential, occasionally breaking up during or immediately after vessel operations. This study aimed to determine the feasibility of using thermopiles, a passive cooling technology, to artificially freeze seawater to “grow” the existing WQB bottomfast-ice edge so that ships can dock directly against it. Finite element simulations using modeling-parameter assumptions indicate that each row of thermopiles can grow a frozen wall to a depth of 9 m in about a month if installed on 1 July with an initial sea-ice thickness of 1 m and a thermopile spacing of 1.5 m. For our simulation scenarios, we approximate that it would take 255 to 820 days to complete a 40 m by 140 m wedge of bottomfast ice. The estimated cost ranges from about $600,000 to $1,600,000. These results serve as a preliminary feasibility study of successfully using thermopiles for generating a direct docking bottomfast-ice wharf at McMurdo.

20 Aug 2020

PUBLICATION NOTICE: Sediment Sorting by Hopper Dredging and Pump-Out Operations: Sampling Methods and Analysis

Abstract: Hopper dredging operations for beach and nearshore placement typically include periods of overflow, which produces some degree of separation between the size fractions of the dredged sediment. The degree of separation and the controlling factors are presently poorly known. This report focuses on laboratory experiments aimed at determining (1) suitable sampling methods on a dredge, (2) composite sampling techniques to reduce analysis cost, (3) associated sampling intervals to achieve suitable sediment representation of a hopper load, and (4) a hydraulic means of sample splitting. Results showed that no statistical difference exists among the three methods used to sample the hopper weir overflow. The method used to sample deposited hopper sediment identified a bias in the percent fines that resulted from flow sheltering. Further, it was found that composited samples were able to quantify the concentration and percent fines accurately, although an analytical data experiment showed that the accuracy of a composited sample is dependent on the sampling intervals. The accuracy of the fines and concentration from a hydraulic sample splitter was found to be dependent on median grain size, with fine sediment being evenly distributed and coarser sediment increasing the error in concentration and grain size distribution.

20 Aug 2020

PUBLICATION NOTICE: Site-Specific Case Studies for Determining Ground Snow Loads in the United States

ABSTRACT:  The U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) has mapped ground snow loads for much of the United States. In some areas where extreme local variations preclude mapping on a national scale, instead of loads, “CS” is used to indicate that Case Studies are needed. This report and the accompanying spreadsheet, which contains the 15,104-station CRREL ground snow load database, provide the information needed to conduct Case Studies. When the latitude, longitude, and elevation of a site of interest are provided, the spreadsheet tabulates data available in the vicinity and generates plots that relate ground snow loads nearby to elevation. With this information, the ground snow load at the site of interest can be determined. This report uses 10 examples to illustrate the methodology and provides our answer and the comments we generate for each of these Case Studies and for 16 additional sites of interest, 8 of which have their answers “disguised” for practice purposes. CRREL has conducted over 1000 Case Studies upon request. Practicing structural engineers were involved in over 250 of them to verify that this methodology is ready to transfer to the design profession.

20 Aug 2020

PUBLICATION NOTICE: Understanding State-of-the-Art Material Classification through Deep Visualization

Abstract: Neural networks (NNs) excel at solving several complex, non-linear problems in the area of supervised learning. A prominent application of these networks is image classification. Numerous improvements over the last few decades have improved the capability of these image classifiers. However, neural networks are still a black-box for solving image classification and other sophisticated tasks. A number of experiments conducted look into exactly how neural networks solve these complex problems. This paper dismantles the neural network solution, incorporating convolution layers, of a specific material classifier. Several techniques are utilized to investigate the solution to this problem. These techniques look at specifically which pixels contribute to the decision made by the NN as well as a look at each neuron’s contribution to the decision. The purpose of this investigation is to understand the decision-making process of the NN and to use this knowledge to suggest improvements to the material classification algorithm.

20 Aug 2020

PUBLICATION NOTICE: Understanding State-of-the-Art Material Classification through Deep Visualization

Abstract: Neural networks (NNs) excel at solving several complex, non-linear problems in the area of supervised learning. A prominent application of these networks is image classification. Numerous improvements over the last few decades have improved the capability of these image classifiers. However, neural networks are still a black-box for solving image classification and other sophisticated tasks. A number of experiments conducted look into exactly how neural networks solve these complex problems. This paper dismantles the neural network solution, incorporating convolution layers, of a specific material classifier. Several techniques are utilized to investigate the solution to this problem. These techniques look at specifically which pixels contribute to the decision made by the NN as well as a look at each neuron’s contribution to the decision. The purpose of this investigation is to understand the decision-making process of the NN and to use this knowledge to suggest improvements to the material classification algorithm.

19 Aug 2020

MKARNS Nav Notice SWL 20-50 Lock 3 Sailing Instruction Lifted

MKARNS - The sailing instruction for the downstream approach to Joe Hardin Lock (No. 3) NM 50.2, as noted in Navigation Notice SWL 20-42 has been lifted.