Behavior of Cementitious Materials under the Effect of an Eco-Cement Based on Dredged Sludge

This paper attempts to simulate the use of green materials from the silt in a dam, and reduce the harmful impacts of siltation on Algerian dams affected by frequent droughts and irregular rainfalls, which are resulted from climate change. These harsh weather conditions are the main cause of water erosion in Algeria, leading to a high silting level in many dams across the country. Therefore, it is necessary to dredge the considerable volumes of sludge in the dam areas. This paper treats the sludge dredged from the K’sob dam, and adds the treated sludge into cement, creating a hybrid binder that can be used in composition of cementitious materials. Specifically, the sludge extracted from the K’sob dam was characterized chemically, physically, mineralogically, and mechanically, and introduced both as a substitute of cement and a component in the mixture of ordinary concrete/mortar. The sludge was firstly activated through calcination, and added to cement at the mass dosages of 10%, 15%, and 20% separately. The mechanical behavior, especially that under compression, of cementitious materials (concrete/mortar) based on the treated sludge was studied through lab tests. The test results show that this technical innovation gives the finished product three major properties, namely, high strength, economy, and a beneficial ecological impact. The results obtained are encouraging and promise an optimal exploitation of the sludge from similar dam areas.

Networks in the balance: an agent-based model of optimal exploitation

Using an agent-based simulation, we illustrate how goal-seeking behavior affects network formation, learning, and performance. Our organization has one manager, who decides where to invest financial capital; individual workers, who decide where to work and prefer projects with larger budgets; and projects, which vary in quality. Our manager discovers high-quality projects from interactions with workers and allocates more capital to high-quality projects. When given an opportunity, our workers move to bigger-budget projects. We let our manager vary in terms of how much she exploits what she learns and allow our workers vary in terms of how sensitive they are to differences in capital. Our results highlight a contingency which shapes how goal-seeking behavior affects learning. The contingency is network fragility. Fragile connections decay quickly when individuals are not working together, while robust relationships decay more slowly. When relationships are robust, exploitation by our manager leads to a dense organizational network, improving information quality, and performance. Decisions by self-interested individuals (our manager and our workers) produce a virtuous learning cycle. When relationships are fragile, exploitation by our manager produces a sparse network, reducing information quality, and undermining performance. When network connections are fragile, the manager must find the right balance of exploitation and exploration, a balance which limits the rate at which workers move from one project to the next, allowing the manager to exploit some of what she knows, without undermining the very network which allows for useful information to be obtained.